{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "8fee91a2-2121-44ef-81b3-11ffc68db20d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "I read in the Census 2020 pop data -- mapped onto 2020 blockgroups\n"
     ]
    }
   ],
   "source": [
    "#THIS FILE: Ohio Congr'l HD, Copy from OH_615COIsnap99\n",
    "#12/1/24 - new for this code is a more general surround operation (incl. embedded but with small neighbors)\n",
    "#  also, we break up queen-contiguous clusters\n",
    "\n",
    "from shapely.geometry import Point, LineString, Polygon, box\n",
    "import shapely\n",
    "import geopandas as gpd\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import ast\n",
    "import time\n",
    "from numpy import random\n",
    "from scipy.stats import norm\n",
    "import math\n",
    "tractPopFile = gpd.read_file(\"state_map_files/oh_pl2020_bg.dbf\")  #use blockgroups for Katy's COI file\n",
    "tractPopFile.head()  #about 40 sec to load\n",
    "print(\"I read in the Census 2020 pop data -- mapped onto 2020 blockgroups\")\n",
    "#handy function for plotting Polygon or multiPolygon tracts and precincts\n",
    "def plotPoly(inputPoly,LW=1):\n",
    "    dummyPoly = Polygon([(0,0),(0,1),(1,1)])\n",
    "    if inputPoly.geom_type == dummyPoly.geom_type:\n",
    "        x,y = inputPoly.exterior.xy\n",
    "        plt.plot(x,y,lw=LW)\n",
    "    else:\n",
    "        for geom in inputPoly.geoms:\n",
    "            if geom.area > 0:  #to avoid error with LineString geom parts\n",
    "                x,y = geom.exterior.xy\n",
    "                plt.plot(x,y,lw=LW)  \n",
    "def plotCenter(t,geom,FONTSIZE=10):\n",
    "    plt.text(geom.centroid.x,geom.centroid.y,t,ha='center',fontsize=FONTSIZE)\n",
    "    \n",
    "def r3(number):\n",
    "    result = round(number,3)\n",
    "    return result\n",
    "\n",
    "def r5(number):\n",
    "    result = round(number,5)\n",
    "    return result\n",
    "\n",
    "def getAdjoiners(UNITLIST, UNITNBRS): #returns all units that neighbor a UNITLIST but are not in the UNITLIST \n",
    "    allNbrs = list()\n",
    "    for U in UNITLIST:\n",
    "        allNbrs = allNbrs + UNITNBRS[U]\n",
    "    adjoiners = list( set(allNbrs).difference(set(UNITLIST)) )\n",
    "    return adjoiners\n",
    "\n",
    "def get2nbrs(ULIST, UNITNBRS):\n",
    "    \"\"\"\n",
    "    Get the combined list of first- and second-level neighbors of a LIST, using neighborList connectivity.  Excludes the source list\n",
    "    \"\"\"\n",
    "    firstList =  getAdjoiners(ULIST, UNITNBRS)\n",
    "    secondList = getAdjoiners(firstList, UNITNBRS)\n",
    "    twoLevelList = list( set(firstList + secondList).difference(set(ULIST) ) )\n",
    "    return twoLevelList\n",
    "\n",
    "def getContigFromStarter(starter, VLIST, NEIGHBORLIST):  #all contiguous units in VLIST, starting from starter unit\n",
    "    foundList, newList, prevList = [ starter ], [ starter ], [ starter ]\n",
    "    while len(newList) > 0:\n",
    "        newList = list()\n",
    "        for V in prevList:\n",
    "            for VV in NEIGHBORLIST[V]:\n",
    "                if VV in VLIST and VV not in foundList:\n",
    "                    newList.append(VV)\n",
    "                    foundList.append(VV)\n",
    "        prevList = newList.copy()        \n",
    "    return foundList   \n",
    "\n",
    "def isContiguous(VLIST,NEIGHBORLIST,returnBiggestPiece=False):\n",
    "    \"\"\"\n",
    "    This method determines if all items in a list form a continuous chain of neighbors based on the passed neighborlist\n",
    "    Empty lists are considered contiguous.  If discontiguous, a less-than-majority piece list is returned,\n",
    "     unless giveBig=True, in which case we return the biggest piece\n",
    "    \"\"\"    \n",
    "    isUnbroken, newList, foundList = True, list(), list()\n",
    "    if len(VLIST) > 0:\n",
    "        foundList, newList, prevList = [ VLIST[0] ], [ VLIST[0] ], [ VLIST[0] ]\n",
    "    while len(newList) > 0:  #this round's list of neighbors\n",
    "        newList = list()\n",
    "        for V in prevList:\n",
    "            for VV in NEIGHBORLIST[V]:\n",
    "                if VV in VLIST and VV not in foundList:\n",
    "                    newList.append(VV)\n",
    "                    foundList.append(VV)\n",
    "        prevList = newList.copy()      \n",
    "    pickedPieceList = foundList.copy()  #default contiguous sublist to pass back to main\n",
    "    \n",
    "    if len(foundList) < len(VLIST):  #not contiguous\n",
    "        isUnbroken  = False\n",
    "        pieceLists, remainingList = [foundList], list( set(VLIST).difference(set(foundList) ) )\n",
    "        if returnBiggestPiece == True:  #we were asked for the biggest piece, not a random small one, so we must find them all\n",
    "            if len(foundList) < 0.5*len(VLIST):\n",
    "                while len(remainingList) > 0:\n",
    "                    newList = getContigFromStarter(remainingList[0], remainingList, NEIGHBORLIST)\n",
    "                    pieceLists.append(newList)\n",
    "                    remainingList = list(set(remainingList).difference(set(newList)))\n",
    "                pieceLengths = [len(pL) for pL in pieceLists]\n",
    "                pickedPieceList = pieceLists[ pieceLengths.index(np.max(pieceLengths)) ]\n",
    "            \n",
    "        else: #quickly return a contiguous sub-list that's at most half the total units in the list\n",
    "            if len(foundList) > 0.5*len(VLIST): #pick a different piece; this one is the majority\n",
    "                pickedPieceList = getContigFromStarter(remainingList[0], remainingList, NEIGHBORLIST)\n",
    "                \n",
    "    return isUnbroken, pickedPieceList\n",
    "\n",
    "def enclaveCheck(UNITLIST,UNITNBRS,maxLoops=2):  #TRY 2 FOR OHIO V2.  USUALLY 4\n",
    "    \"\"\"\n",
    "    This method determines if a list of units has an unbroken boundary AND whether its complement has an unbroken boundary\n",
    "    If the complement boundary is broken, there is an enclave or the district is so disconnected its adjoining units aren't contiguous\n",
    "    The method returns contiguity of boundary and of its adjoiners.  Also returns the lists of boundary and complement-boundary units\n",
    "      If either of these is broken, only a contiguous sublist is returned that is guaranteed to be smaller than half (for finding enclaves)\n",
    "      maxLoops is the number of loops for expanding neighbors-of-neighbors for contiguity of the units outside the passed unit-list\n",
    "    \"\"\"\n",
    "    UNITSET = set(UNITLIST)\n",
    "    ADJLIST =  get2nbrs(UNITLIST, UNITNBRS)  #in case direct adjoiners are only queen-adjacent\n",
    "    #adjoinersOfAdjoiners = getAdjoiners(ADJLIST,  UNITNBRS)\n",
    "    #BDRYLIST = list( set(UNITLIST).intersection(set(adjoinersOfAdjoiners)) )  #this might fail for queen-adjacent boundary units\n",
    "    BDRYLIST = list (set(get2nbrs(ADJLIST,UNITNBRS)).intersection(UNITSET) )  #in case inHD boundary is only queen-adjacent\n",
    "    noEnclave, enclaveList =   isContiguous(ADJLIST, UNITNBRS)  \n",
    "    unbroken, smallPieceList = isContiguous(BDRYLIST, UNITNBRS)\n",
    "    if not unbroken: #could be that district's boundary intersects the state boundary or there is a nonHD enclave inside the HD\n",
    "        unbroken, smallPieceList = isContiguous(UNITLIST, UNITNBRS)  #slower check for full district, not just its boundary \n",
    "    nLoops = 1 #could be that fragmented adjoining districts are underestimating true contiguity.  Widen the contig search\n",
    "    while nLoops <= maxLoops and not noEnclave:\n",
    "        nLoops +=1\n",
    "        newSet = set(ADJLIST)\n",
    "        for UU in ADJLIST:\n",
    "            newSet = newSet.union( set(UNITNBRS[UU]).difference(UNITSET) )\n",
    "        ADJLIST = list(newSet)\n",
    "        noEnclave, enclaveList =   isContiguous(ADJLIST, UNITNBRS)\n",
    "    #isJiggy = noEnclave and unbroken\n",
    "    return unbroken, noEnclave, smallPieceList, enclaveList\n",
    "\n",
    "def getBdryNonEdgers(UNITLIST, UNITNBRS): #all in-district boundary units that neighbor a non-district unit\n",
    "    ALLnonHDnbrs = set()\n",
    "    for UUU in UNITLIST:\n",
    "        ALLnonHDnbrs = ALLnonHDnbrs.union(set(UNITNBRS[UUU])).difference(set(UNITLIST))\n",
    "    BdryNonEdgerSet = set()\n",
    "    for UUU in UNITLIST:\n",
    "        if len(set(UNITNBRS[UUU]).intersection(ALLnonHDnbrs)) > 0:\n",
    "            BdryNonEdgerSet.add(UUU)\n",
    "    return list(BdryNonEdgerSet)\n",
    "\n",
    "def getEnclaveLists(UNITLIST, UNITNBRS):\n",
    "    \"\"\"\n",
    "    finds ALL units enclaved by a UNITLIST, parsed into lists of contiguous pieces\n",
    "    We assume the largest contiguous complement to the UNITLIST is not an enclave, but rather the majority of the HD complement\n",
    "    if the UNITLIST's complement (all couldBeEnclaved) is contiguous, the returned list will be blank\n",
    "    \"\"\"\n",
    "    eSets, nU = list(), len(UNITNBRS)\n",
    "    offmapList = list()\n",
    "    for i,L in enumerate(UNITNBRS):\n",
    "        if len(L) == 0:\n",
    "            offmapList.append(i)  #offmap list are units with no neighbors (were surrounded)\n",
    "    complementSet = set([i for i in range(nU)] ).difference( set(UNITLIST + offmapList) )    \n",
    "    remaining2nbrs = get2nbrs(UNITLIST, UNITNBRS)\n",
    "    \n",
    "    isContig, shortList = isContiguous(remaining2nbrs,UNITNBRS) #quicker than contig check on entire complement\n",
    "    while not isContig:  #this will kick out before writing the final sublist = map majority\n",
    "        starter = shortList[0]\n",
    "        newEnclaveList = getContigFromStarter(starter, list(complementSet), UNITNBRS)\n",
    "        eSets.append(set(newEnclaveList))\n",
    "        remaining2nbrs = list(set(remaining2nbrs).difference(set(shortList)) )\n",
    "        isContig, shortList = isContiguous(remaining2nbrs,UNITNBRS)\n",
    "        \n",
    "        # couldBeEnclaved = list( set(couldBeEnclaved).difference(set(newEnclaveList)) )  #revised 18-Feb-24 -- was slower\n",
    "    fused_eSets = set()\n",
    "    for i, eSet in enumerate(eSets):\n",
    "        fused_eSets = fused_eSets.union(eSet)\n",
    "        for j in range(i+1, len(eSets) ) :\n",
    "            eSets[j] = eSets[j].difference(eSet)  #in case contiguity occurs, but not in 2-neighbor list; avoid double-count\n",
    "    remnant_eSet = complementSet.difference(fused_eSets) \n",
    "    eLengths = [len(eSet) for eSet in eSets]\n",
    "    if len(eSets) > 0:\n",
    "        if len(remnant_eSet) < np.max(eLengths):  #exchange the small remnant for the biggest found \"enclave\" (usually the major complement) \n",
    "            eSets[eLengths.index(np.max(eLengths))] = remnant_eSet.copy()\n",
    "    eLists = [list(eSet) for eSet in eSets]\n",
    "    return eLists\n",
    "\n",
    "def wontEnclave(proposedU, dList, NBRLIST, mapBDRYLIST):  #TRY MAXLOOPS = 3 FOR OH REDO, NOT USUAL 6\n",
    "    \"\"\"\n",
    "    This method checks if adding a proposedU to a dList (list of units in a district) will create an \"enclave\" of units in the dList's complement\n",
    "    via two problems:  A) the dList will now have a discontiguous set of units on the map boundary.  The full map boundary list is mapBDRYLIST\n",
    "      B) The non-dList neighbors of dList units aren't contiguous\n",
    "    The method doesn't require that the dList wontEnclave without the proposedU included; it just checks the proposedU + dList combination\n",
    "    It also doesn't check that the dList is itself contiguous with or without proposedU\n",
    "    In that sense, it is more limited than enclaveCheck\n",
    "    \"\"\"\n",
    "    wontEnclave = True\n",
    "    newList, newSet = dList + [proposedU], set(dList + [proposedU])\n",
    "    unitsOnBoundary = list( set(mapBDRYLIST).intersection(newSet) )\n",
    "    wontEnclave, __ = isContiguous(unitsOnBoundary,NBRLIST)  #first check - does district touch MAP boundary in multiple places? (quick FAIL)\n",
    "    if wontEnclave: #slower check below for internal enclaves\n",
    "        adjoiners = get2nbrs(newList, NBRLIST)  #2-level to protect for queen adjacency in boundary        \n",
    "        wontEnclave, __ = isContiguous(adjoiners,NBRLIST)\n",
    "        if not wontEnclave:\n",
    "            nLoops = 1 #could be that fragmented adjoining districts are underestimating true contiguity.  Widen the contig search\n",
    "            maxLoops, ADJLIST = 3, adjoiners #unlike enclaveCheck, here we just arbitrarily set a number of loops for search expansion\n",
    "            while nLoops <= maxLoops and not wontEnclave:\n",
    "                nLoops +=1\n",
    "                adjSet = set(ADJLIST)  #align nomenclature w enclaveCheck\n",
    "                for UU in ADJLIST:\n",
    "                    adjSet = adjSet.union( set(NBRLIST[UU]).difference(set(newList)) )\n",
    "                ADJLIST = list(adjSet)\n",
    "                wontEnclave, __ =   isContiguous(ADJLIST, NBRLIST)\n",
    "        \n",
    "    return wontEnclave\n",
    "\n",
    "def isRookAdj(geo1, geo2):  #intersection with rook (not queen) adjacency\n",
    "    isRookAdj = False\n",
    "    if geo1.intersects(geo2):\n",
    "        if (geo1.intersection(geo2)).geom_type != Point(0,0).geom_type:\n",
    "            isRookAdj = True\n",
    "    return isRookAdj\n",
    "\n",
    "def getWeightedAvgAndSD(LIST, WEIGHTS):\n",
    "    nWeights = len(WEIGHTS)\n",
    "    normWeights = [WEIGHTS[i] / np.sum(WEIGHTS) for i in range(nWeights) ]\n",
    "    AVG = 0.\n",
    "    for i, value in enumerate(LIST):\n",
    "        AVG += normWeights[i] * value\n",
    "    sumVar = 0.\n",
    "    for i, value in enumerate(LIST):\n",
    "        sumVar += normWeights[i] * (value - AVG)**2\n",
    "    SD = sumVar ** 0.5     #don't need to normalize again since weights were normalized\n",
    "    return AVG, SD\n",
    "\n",
    "def getHDcp(TRACTCP,TRACTPOP, TRACTLIST, SPLITTRACTNO = -777,SPLITTRACTUSE = 1.):  #population centerpoint of a Home District or county (cluster)\n",
    "    cpx, cpy, sumPop = 0.,0., 0.\n",
    "    for tt in TRACTLIST:\n",
    "        USE = 1.\n",
    "        if tt ==    SPLITTRACTNO:\n",
    "            USE =   SPLITTRACTUSE\n",
    "        sumPop += USE*TRACTPOP[tt]\n",
    "        cpx +=    USE*TRACTPOP[tt] * TRACTCP[tt].x\n",
    "        cpy +=    USE*TRACTPOP[tt] * TRACTCP[tt].y\n",
    "    HDCP_ = Point(cpx/sumPop, cpy/sumPop)\n",
    "    return HDCP_\n",
    "\n",
    "dummyPoly = Polygon([(0,0),(0,1),(1,1)])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "a9e2fbed-247e-4a00-be18-5507b7e2b88f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "there are 9472 building blocks for OH\n"
     ]
    }
   ],
   "source": [
    "# EXTRACT TRACT GEOMETRIES AND POPULATIONS INTO LISTS, COMPUTE TRACT AREAS\n",
    "STATE = \"OH\"\n",
    "tractGeom = tractPopFile['geometry']  #for some states, replace with tractGeomFile\n",
    "tractPop = tractPopFile['P0010001']\n",
    "tractVAP = tractPopFile['P0030001']   #NEW 3/2/22 - USE VAP\n",
    "# tractPop2 = tractPopFile['P0020001']   #not needed; confirmed that this matches P00100001 exactly\n",
    "tractHisp = tractPopFile['P0040002']   #NEW 3/2/22 - USE VAP\n",
    "tractBlack = tractPopFile['P0030004']  #NEW 3/2/22 - USE VAP\n",
    "tractCountyNo = tractPopFile['COUNTYFP20']\n",
    "GEOID20 = tractPopFile['GEOID20']\n",
    "nTracts = len(tractPop)\n",
    "tractCP = [tractGeom[t].centroid for t in range(nTracts)]\n",
    "nVTDs = nTracts #nomenclature\n",
    "print(\"there are {0} building blocks for {1}\".format(nTracts, STATE) )\n",
    "tractArea = [0.]*nTracts\n",
    "tractCountyNo = tractCountyNo.to_numpy()\n",
    "countyNo = [0]*nTracts\n",
    "for t in range (0,nTracts) :  #from odd-numbered counties in US Census list to integer list\n",
    "    tractArea[t] = tractGeom[t].area\n",
    "    countyNo[t] = int((int(tractCountyNo[t]) - 1)/2)\n",
    "isSkippedTract = [0] *nTracts  #this will house a temporary list of tracts for manipulation\n",
    "tractPop = tractPop.to_numpy()  #to avoid panda overwrite grousing\n",
    "tractBlack= tractBlack.to_numpy()\n",
    "tractHisp = tractHisp.to_numpy()\n",
    "tractVAP = tractVAP.to_numpy()\n",
    "stateVAP = np.sum(tractVAP)\n",
    "nCounties = int( np.max(countyNo)+1)\n",
    "skipList = [6080, 3774, 9049, 2675, 6268, 8741]\n",
    "for t in skipList : #coastal bgs for Ohio already known\n",
    "    isSkippedTract[t] = 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "a619e262-3e70-4945-87b1-58245cc514c4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "working on tract 0\n",
      "working on tract 1000\n",
      "working on tract 2000\n",
      "working on tract 3000\n",
      "working on tract 4000\n",
      "working on tract 5000\n",
      "working on tract 6000\n",
      "working on tract 7000\n",
      "working on tract 8000\n",
      "working on tract 9000\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# CREATE COUNTY-LEVEL MAP OF THIS STATE - excluding lakeshore tracts from county building\n",
    "for s in skipList :\n",
    "    countyNo[s] = -999  #don't count these lakeshore tracts as part of a county\n",
    "dummyPoly = Polygon([ (0,0),(1,0),(1,1)])\n",
    "countyGeom = [dummyPoly]*nCounties\n",
    "lakeErieGeom = []\n",
    "countyPop = [0.]*nCounties\n",
    "nCountyTracts = [0]*nCounties  #how many tracts found in this county\n",
    "countyTractList = [list() for c in range(nCounties) ]\n",
    "for t in range(nTracts):  #now loop through tracts, assign each to county, build county polygons\n",
    "    if t%1000 == 0:\n",
    "        print(\"working on tract\",t)\n",
    "    if t not in skipList:\n",
    "        c = int(countyNo[t])\n",
    "        countyTractList[c].append(t)\n",
    "        nCountyTracts[c] +=1   #found another tract that belongs to this county\n",
    "        countyPop[c] += tractPop[t]\n",
    "        if nCountyTracts[c] == 1:  #this is the first tract found for this county\n",
    "            countyGeom[c] = tractGeom[t]  #seed the county geometry polygon\n",
    "        else:\n",
    "            countyGeom[c] = countyGeom[c].union(tractGeom[t])\n",
    "countyMAP = countyGeom[0]\n",
    "for c in range(nCounties):  #now build the state map from the counties\n",
    "    plotPoly(countyGeom[c])\n",
    "    plotCenter(c,countyGeom[c],8)\n",
    "    countyMAP = countyMAP.union(countyGeom[c])\n",
    "plotPoly(countyMAP)\n",
    "plt.show()   "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "cda12941-0eef-4a29-a376-dd0d4bc2927b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "15 districts, each with avgDistrictPop of 786629.867\n",
      "I will now build a map from the counties and display the whole county districts\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "there are a total of 65 small or perfect counties that we would keep whole in county-snapped Home Districts\n"
     ]
    }
   ],
   "source": [
    "#quick block to flag the whole county-districts\n",
    "MAP = dummyPoly\n",
    "perfectCounty = [0]*nCounties  #\"perfect\" counties have the perfect population for a whole district\n",
    "wholeCounty = [0]*nCounties    #\"whole\" counties are either perfect or small enough that they should be kept whole\n",
    "minCountyRatio = 0.15   #small counties will naturally be unsplit.  We'll set a reasonable arbitrary threshold.\n",
    "lockedTract = [0]*nTracts\n",
    "nDistricts = 15 #Ohio Congressional\n",
    "statePop = np.sum(tractPop)\n",
    "avgDistrictPop = statePop/nDistricts\n",
    "aDP = avgDistrictPop\n",
    "maxDevn = 0.05\n",
    "print(nDistricts,\"districts, each with avgDistrictPop of\",r3(avgDistrictPop))\n",
    "print(\"I will now build a map from the counties and display the whole county districts\")\n",
    "for c in range(nCounties):\n",
    "    if MAP == dummyPoly:\n",
    "        MAP = countyGeom[c]\n",
    "    else:\n",
    "        MAP = MAP.union(countyGeom[c])\n",
    "    if countyPop[c] >= (1.-maxDevn)*avgDistrictPop and countyPop[c] <= (1.+maxDevn)*avgDistrictPop :\n",
    "        perfectCounty[c] = 1\n",
    "        wholeCounty[c] = 1\n",
    "        plotPoly(countyGeom[c])\n",
    "    if countyPop[c] < minCountyRatio*avgDistrictPop:  #small counties will naturally be unsplit.\n",
    "        wholeCounty[c] = 1\n",
    "plotPoly(MAP)\n",
    "plt.show()\n",
    "print(\"there are a total of\",np.sum(wholeCounty),\"small or perfect counties that we would keep whole in county-snapped Home Districts\")\n",
    "for t in range(nTracts):\n",
    "    if isSkippedTract == 0:\n",
    "        if wholeCounty[countyNo[t]] == 1:  #this tract is part of a whole county per Article XI.3.c.2\n",
    "            lockedTract[t] = 1             # ... or in a county that is so small we are keeping that county whole"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "3b120267-0b65-4e93-8cbb-fd8d03a5006e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "below is copied from OH_COI_org615legis\n",
      "there were 45 blockgroups with tractPop < 10\n",
      "I read in GEOID and clusterID for each of 9435 blockgroups. We expected 9427\n",
      "...assuming bg's w pop < 10 were not SKATER-assigned.  But there are a total of 9466 nonskipped bgs\n",
      "after merging, we are left with 9435 active blockgroups\n",
      "working on adding bg 0 to a COI cluster\n",
      "working on adding bg 2000 to a COI cluster\n",
      "working on adding bg 4000 to a COI cluster\n",
      "working on adding bg 6000 to a COI cluster\n",
      "working on adding bg 8000 to a COI cluster\n",
      "I formed 615 COI shapes.  Now I plot them.\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "I will now check if any skipped tracts are in the BG assignment list\n",
      "tract 6080 with low pop 0 was assigned to COI -999 and county -999\n",
      "tract 3774 with low pop 0 was assigned to COI -999 and county -999\n",
      "tract 9049 with low pop 0 was assigned to COI -999 and county -999\n",
      "tract 2675 with low pop 0 was assigned to COI -999 and county -999\n",
      "tract 6268 with low pop 0 was assigned to COI -999 and county -999\n",
      "tract 8741 with low pop 0 was assigned to COI -999 and county -999\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"below is copied from OH_COI_org615legis\")\n",
    "nLowPopTracts, minTractPop = 0,10\n",
    "for t in range(nTracts):\n",
    "    if tractPop[t] < minTractPop:\n",
    "        nLowPopTracts += 1\n",
    "print(\"there were\", nLowPopTracts,\"blockgroups with tractPop <\",minTractPop)\n",
    "#READ IN blockgroup COI assignments (FROM Katy)\n",
    "COIfile = pd.read_csv(\"state_map_files/OH_ClustersbyBG_SD16Dec.csv\")  #or ..._SC.csv\n",
    "COI_GEOID = COIfile['GEOID']\n",
    "COIgeoid = [str(COI_GEOID[i]) for i in range(len(COI_GEOID)) ]  #pd had interpreted geoid's as nos\n",
    "clusterID = COIfile['CLUSTER_ID']  #Katy numbers these 1-1850 or 1 - 615\n",
    "clusterID = clusterID.to_numpy()\n",
    "print(\"I read in GEOID and clusterID for each of\",len(clusterID),\"blockgroups. We expected\",nTracts-nLowPopTracts)\n",
    "print(\"...assuming bg's w pop <\",minTractPop,\"were not SKATER-assigned.  But there are a total of\",nTracts-len(skipList),\"nonskipped bgs\")\n",
    "nClusters = np.max(clusterID) - np.min(clusterID) + 1\n",
    "for i in range(len(clusterID)):\n",
    "    clusterID[i] -= 1   #renumber these starting at zero\n",
    "COIdf = pd.DataFrame( {\"GEOID20\":COIgeoid,\"clusterID\":clusterID } )\n",
    "#quick little dataframe since the COI file excludes some tracts ************************\n",
    "origTractNo = [i for i in range(nTracts)]\n",
    "miniTractPopFile = pd.DataFrame( {\"GEOID20\":GEOID20,\"origTractNo\":origTractNo} )\n",
    "mergedDF = pd.merge(miniTractPopFile,COIdf,on=\"GEOID20\")\n",
    "tractNo = mergedDF['origTractNo']\n",
    "mergedClusterID = mergedDF['clusterID']\n",
    "nActiveTracts = len(tractNo)\n",
    "print(\"after merging, we are left with\",nActiveTracts,\"active blockgroups\")\n",
    "nCOIs = nClusters  \n",
    "COIgeom = [dummyPoly]*nCOIs   #again, common language\n",
    "COIarea = [0.]*nCOIs\n",
    "muniTractList = [list()]*nCOIs\n",
    "tractMuniNo = [-999]*nTracts\n",
    "\n",
    "for s in range(nCOIs):\n",
    "    muniTractList[s] = list()\n",
    "\n",
    "for fakeT in range(nActiveTracts):\n",
    "    t = tractNo[fakeT]  #t is the true tractNo in the original tractPopFile for the mergedDF's row no (fake tract no)\n",
    "    if t%2000 == 0 :\n",
    "        print(\"working on adding bg\",t,\"to a COI cluster\")\n",
    "    s = mergedClusterID[fakeT]\n",
    "    tractMuniNo[t] = s\n",
    "    muniTractList[s].append(t)\n",
    "    if COIgeom[s] == dummyPoly:\n",
    "        COIgeom[s] = tractGeom[t]\n",
    "    else:\n",
    "        COIgeom[s] = COIgeom[s].union(tractGeom[t])\n",
    "print(\"I formed\",nCOIs,\"COI shapes.  Now I plot them.\")\n",
    "for c in range(nCOIs):\n",
    "    plotPoly(COIgeom[c])\n",
    "    COIarea[c] = COIgeom[c].area\n",
    "plt.show()\n",
    "\n",
    "print(\"I will now check if any skipped tracts are in the BG assignment list\")\n",
    "for t in skipList:\n",
    "    if t in tractNo:\n",
    "        print(\"tract\",t,\"with low pop\",tractPop[t],\"was assigned to COI\",tractMuniNo[t],\"and county\",countyNo[t])\n",
    "        plotPoly(tractGeom[t])\n",
    "        if tractMuniNo[t] >= 0:\n",
    "            plotPoly(COIgeom[tractMuniNo[t]])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "dd77e2a7-0a5e-4426-a703-7d092b482d0d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There were a total of 31 low-pop non-coastal bgs not SKATER-assigned to a COI\n",
      "I will now assign them to the contiguous COI with the closest centroid\n",
      "[747, 1102, 1103, 1225, 2302, 2802, 2859, 2881, 2970, 2972, 3593, 3902, 4107, 5467, 5469, 5490, 5496, 5551, 5599, 5600, 5627, 5631, 6800, 6805, 7048, 8077, 8789, 8879, 9293, 9312, 9375]\n"
     ]
    }
   ],
   "source": [
    "missedBGlist = list()\n",
    "for b in range(nTracts):\n",
    "    if b not in skipList and tractMuniNo[b] < 0:\n",
    "        missedBGlist.append(b)\n",
    "print(\"There were a total of\",len(missedBGlist),\"low-pop non-coastal bgs not SKATER-assigned to a COI\")\n",
    "print(\"I will now assign them to the contiguous COI with the closest centroid\")\n",
    "for b in missedBGlist:\n",
    "    closeCOIs = list()\n",
    "    for c in range(nCOIs):\n",
    "        if isRookAdj(tractGeom[b],COIgeom[c]):\n",
    "            closeCOIs.append(c)\n",
    "    closeDists = [tractGeom[b].distance(COIgeom[c].centroid) for c in closeCOIs]\n",
    "    cc = closeCOIs[closeDists.index(np.min(closeDists))]\n",
    "    tractMuniNo[b] = cc\n",
    "    muniTractList[cc].append(b)\n",
    "    COIgeom[cc] = COIgeom[cc].union(tractGeom[b])\n",
    "\n",
    "for b in range(nTracts):\n",
    "    if tractMuniNo[b] < 0 and b not in skipList:\n",
    "        plotPoly(tractGeom[b])\n",
    "        print(\"unassigned noncoastal blockgroup\",b,countyNo[b],tractPop[b])\n",
    "print(missedBGlist)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "0c20199f-a1d1-4c15-b71e-da0c7702aba5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "showing the counties where we assigned BGs missing from original COI list\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"showing the counties where we assigned BGs missing from original COI list\")\n",
    "for c in range(nCounties):\n",
    "    LIST = set(missedBGlist).intersection(set(countyTractList[c]))\n",
    "    if len(LIST) > 0:\n",
    "        for i,b in enumerate(LIST):\n",
    "            plotPoly(tractGeom[b])\n",
    "            plotCenter(b,tractGeom[b])\n",
    "            plotPoly(COIgeom[tractMuniNo[b]])\n",
    "        plotPoly(countyGeom[c],0.1)\n",
    "        plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "be4c1dbd-15a1-45dd-b185-d3af5522b1c6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "here is a histogram of number of bgs per COI\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "the minimum number of bgs in a COI is 1\n"
     ]
    }
   ],
   "source": [
    "print(\"here is a histogram of number of bgs per COI\")\n",
    "plt.hist([len(muniTractList[u]) for u in range(nCOIs)],bins = [0,1,3,10,30,300,1000] )\n",
    "plt.show()\n",
    "plt.scatter([u for u in range(nCOIs)], [len(muniTractList[u]) for u in range(nCOIs)] )\n",
    "plt.show()\n",
    "print(\"the minimum number of bgs in a COI is\",np.min([len(muniTractList[u]) for u in range(nCOIs)]) )"
   ]
  },
  {
   "cell_type": "raw",
   "id": "d819ca83-0d51-417d-aa82-956a7c0b1abb",
   "metadata": {},
   "source": [
    "## BELOW BLOCKS WOULD BE TURNED ON IF WE CONVERTED COI'S TO VTD-BASED.  LEAVE AS BG-BASED\n",
    "print(\"We will now map COIgeoms onto vtd's, for easier snapping to HDvtdLists later\")\n",
    "vtdPopFile = gpd.read_file(\"state_map_files/oh_pl2020_vtd.dbf\")  #use vtd's directly"
   ]
  },
  {
   "cell_type": "raw",
   "id": "77520f70-88b7-4284-9af0-ea1b4b0afb99",
   "metadata": {},
   "source": [
    "vtdGeom = vtdPopFile['geometry'] \n",
    "vtdPop = vtdPopFile['P0010001'].to_numpy()\n",
    "vtdCN = vtdPopFile['COUNTYFP20']\n",
    "vtdCountyNo = list()\n",
    "for v in range(nVTDs):\n",
    "    vtdCountyNo.append( int((int(vtdCN[v]) - 1)/2) )"
   ]
  },
  {
   "cell_type": "raw",
   "id": "217ff8bf-fd6b-45c8-ae4c-0b204ac2ab78",
   "metadata": {},
   "source": [
    "print(\"prepping the vtd stats\")\n",
    "vtdGeom = vtdPopFile['geometry'] \n",
    "vtdPop = vtdPopFile['P0010001'].to_numpy()\n",
    "vtdCountyNo = vtdPopFile['COUNTYFP20']\n",
    "nVTDs = len(vtdPop)\n",
    "print(\"there are {0} vtds for {1}\".format(nVTDs, STATE) )\n",
    "vtdArea = [0.]*nVTDs\n",
    "vtdCountyNo = vtdCountyNo.to_numpy()\n",
    "for t in range (0,nVTDs) :  #from odd-numbered counties in US Census list to integer list\n",
    "    vtdArea[t] = vtdGeom[t].area\n",
    "    vtdCountyNo[t] = int((int(vtdCountyNo[t]) - 1)/2)\n",
    "isSkippedVTD = [0] *nVTDs  #this will house a temporary list of tracts for manipulation\n",
    "skippedVTDs = [8197, 4634, 3730, 4458, 840, 2974, 1008]\n",
    "for v in skippedVTDs:\n",
    "    isSkippedVTD[v] = 1\n",
    "countyVTDlist = [list() for c in range(nCounties)]\n",
    "for v in range(nVTDs):\n",
    "    if v not in skippedVTDs:\n",
    "        countyVTDlist[vtdCountyNo[v]].append(v)\n",
    "VTDcp = [vtdGeom[v].centroid for v in range(nVTDs)]"
   ]
  },
  {
   "cell_type": "raw",
   "id": "889f2243-cf20-4a99-9be1-94ac53208e6f",
   "metadata": {},
   "source": [
    "print(\"and now we map COIs...\")\n",
    "COIvtdList = [list() for u in range(nCOIs)]\n",
    "for u in range(nCOIs):\n",
    "    if u %100 == 0:\n",
    "        print(\"assigning vtds to COI geom\",u)\n",
    "    for c in range(nCounties):\n",
    "        if countyGeom[c].intersects(COIgeom[u]):\n",
    "            for v in countyVTDlist[c]:\n",
    "                if COIgeom[u].contains(VTDcp[v]):\n",
    "                    COIvtdList[u].append(v)"
   ]
  },
  {
   "cell_type": "raw",
   "id": "1e3a9072-5f45-41f3-a514-4386b9f07971",
   "metadata": {},
   "source": [
    "nAssigned = np.sum([len(COIvtdList[u]) for u in range(nCOIs) ])\n",
    "print(\"out of\",nVTDs,\"we assigned\",nAssigned,\"and there are\",len(skippedVTDs),\"skips\")\n",
    "unassigneds = list()\n",
    "for v in range(nVTDs):\n",
    "    if v not in skippedVTDs:\n",
    "        found = False\n",
    "        for u in range(nCOIs):\n",
    "            if v in COIvtdList[u]:\n",
    "                found = True\n",
    "                break\n",
    "        if not found:\n",
    "            unassigneds.append(v)\n",
    "print(\"the following vtds were not assigned\",unassigneds)\n",
    "for v in unassigneds:\n",
    "    COIdist = [VTDcp[v].distance(COIgeom[u]) for u in range(nCOIs) ]\n",
    "    u = COIdist.index(np.min(COIdist))\n",
    "    print(\"assigning vtd\",v,\"to closest COI\",u)\n",
    "    COIvtdList[u].append(v)"
   ]
  },
  {
   "cell_type": "raw",
   "id": "6b3c1823-511e-43cd-beab-025cecb686f3",
   "metadata": {},
   "source": [
    "print(\"eliminating COIs that captured no vtds\")\n",
    "nOldCOIs, oldLists = nCOIs, [COIvtdList[u] for u in range(nCOIs)]\n",
    "COIvtdList = list()\n",
    "for u in range(nOldCOIs):\n",
    "    if len(oldLists[u]) > 0:\n",
    "        COIvtdList.append(oldLists[u])\n",
    "nCOIs = len(COIvtdList)\n",
    "COIpop = [np.sum([vtdPop[v] for v in COIvtdList[u] ]) for u in range(nCOIs)]\n",
    "print(\"after ditching these, we have\",nCOIs,\"with a total pop of\",np.sum(COIpop),\"vs statePop\",statePop)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "969dbd0a-31fa-43ed-9dd0-2d9ba9df1c5e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now determine the county topology\n"
     ]
    }
   ],
   "source": [
    "print(\"Now determine the county topology\")\n",
    "countyNeighbors = [list() for c in range(nCounties)]\n",
    "for c in range(nCounties):\n",
    "    for cc in range(c+1, nCounties):\n",
    "        if isRookAdj(countyGeom[c],countyGeom[cc]):\n",
    "            countyNeighbors[c].append(cc)\n",
    "            countyNeighbors[cc].append(c)\n",
    "mainMAP = countyMAP.geoms[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "cf28a7ff-6138-42fe-9e38-9c1e11b2ebf3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Option 1: we read in the bg topology\n",
      "I read in the blockgroup topology; there are 9472 blockgroups and state pop of 11799448\n"
     ]
    }
   ],
   "source": [
    "print(\"Option 1: we read in the bg topology\")  #already connects Kelleys Island to mainland\n",
    "infile = \"./state_map_files/OH99mod_bgTopologies_17Nov24.csv\"\n",
    "bgDF = pd.read_csv(infile)\n",
    "tractCPx = bgDF[\"centroid x\"]\n",
    "tractCPy = bgDF[\"centroid y\"]\n",
    "tractPop = bgDF[\"bgPop\"]\n",
    "bgNbrList = bgDF[\"bgNbrs\"]\n",
    "countyNo = bgDF[\"countyNo\"]\n",
    "isBorderBG = bgDF[\"isBorderBG\"]\n",
    "borderBGs = list()\n",
    "for b in range(len(isBorderBG)):\n",
    "    if isBorderBG[b] == 1:\n",
    "        borderBGs.append(b)\n",
    "nTracts = len(tractPop)\n",
    "statePop = np.sum(tractPop)\n",
    "#bgNbrs = bgNbrList.copy()\n",
    "bgNbrs = [ast.literal_eval(bgNbrList[t]) for t in range(nTracts) ]\n",
    "print(\"I read in the blockgroup topology; there are\",nTracts,\"blockgroups and state pop of\",statePop)"
   ]
  },
  {
   "cell_type": "raw",
   "id": "366492ad-ee61-412c-86ec-b358a9dc35f9",
   "metadata": {},
   "source": [
    "print(\"Option 2: Determine the bg topology -- SKIP IF WE WANT TO READ IN ABOVE INSTEAD\")\n",
    "bgNbrs = [list() for v in range(nTracts)]\n",
    "for c in range(nCounties):\n",
    "    if c%10 == 0:\n",
    "        print(\"working on bg neighbors in county\",c)\n",
    "    for v in countyTractList[c]:\n",
    "        for vv in set(countyTractList[c]).difference({v}):\n",
    "            if isRookAdj(tractGeom[vv], tractGeom[v]):\n",
    "                bgNbrs[v].append(vv)\n",
    "        for cc in countyNeighbors[c]:\n",
    "            if isRookAdj(countyGeom[cc],tractGeom[v]):\n",
    "                for vv in countyTractList[cc]:\n",
    "                    if isRookAdj(tractGeom[vv], tractGeom[v]):\n",
    "                        bgNbrs[v].append(vv)\n",
    "for v in countyTractList[21]:\n",
    "    plotPoly(tractGeom[v])\n",
    "    plotCenter(v,tractGeom[v])\n",
    "print(\"finding Kelleys Island\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "raw",
   "id": "754b8ca4-4e6e-4d4d-b1d2-b941c188cc84",
   "metadata": {},
   "source": [
    "print(\"Continuing option 2: manually connecting Kelleys Island bg to mainland\")\n",
    "Kelley, Knbrs = 5879, [5870, 5871]\n",
    "for bg in Knbrs:\n",
    "    bgNbrs[Kelley].append(bg)\n",
    "    bgNbrs[bg].append(Kelley)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "4bdfdde5-bf1e-4710-9115-70567c5c8fdb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "compute and plot the COI pops by area\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "there are 3 COIs with pop > 1.05 * 786629.8666666667\n",
      "rebuilding COIgeom from bgs for COI 0\n",
      "rebuilding COIgeom from bgs for COI 100\n",
      "rebuilding COIgeom from bgs for COI 200\n",
      "rebuilding COIgeom from bgs for COI 300\n",
      "rebuilding COIgeom from bgs for COI 400\n",
      "rebuilding COIgeom from bgs for COI 500\n",
      "rebuilding COIgeom from bgs for COI 600\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "COItractList = [muniTractList[c].copy() for c in range(nCOIs)]  #nomenclature\n",
    "print(\"compute and plot the COI pops by area\")\n",
    "COIpop =  [np.sum([tractPop[t] for t in COItractList[u] ]) for u in range(nCOIs)]\n",
    "COIarea = [np.sum([tractArea[t] for t in COItractList[u] ]) for u in range(nCOIs)]\n",
    "plt.scatter(COIarea,COIpop)\n",
    "plt.axhline(aDP,ls=\"--\")\n",
    "plt.show()\n",
    "isBigCOI, bigCOIlist = [0]*nCOIs,list()\n",
    "for u in range(nCOIs):\n",
    "    if COIpop[u] > 1.01 * aDP:\n",
    "        isBigCOI[u] = 1\n",
    "        bigCOIlist.append(u)\n",
    "nBigCOIs = len(bigCOIlist)\n",
    "print(\"there are\",nBigCOIs,\"COIs with pop > 1.05 *\",aDP)\n",
    "COIgeom = [tractGeom[COItractList[u][0]] for u in range(nCOIs)]\n",
    "for u in range(nCOIs):\n",
    "    if u%100 == 0:\n",
    "        print(\"rebuilding COIgeom from bgs for COI\",u)\n",
    "    for v in COItractList[u]:\n",
    "        COIgeom[u] = COIgeom[u].union(tractGeom[v])\n",
    "for c in bigCOIlist:\n",
    "    plotPoly(COIgeom[c])\n",
    "    plotCenter(r3(COIpop[c]/aDP), COIgeom[c])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "6e1c8383-3d2e-4f64-90ac-f7eecfe246cb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now create units.  All 3 big COIs will be split into their component bgs\n",
      "splitting COI 0 with pop 843859\n",
      "splitting COI 70 with pop 1287365\n",
      "splitting COI 332 with pop 1175959\n",
      "we now have 3126 units from the original 615 COIs\n",
      "total number of bg assignments plus skips are now 9472\n"
     ]
    }
   ],
   "source": [
    "print(\"Now create units.  All\",nBigCOIs,\"big COIs will be split into their component bgs\")\n",
    "unitPop, unitGeom, unitTractList, unitCP, unitOrigCOIno = list(), list(), list(), list(), list()\n",
    "for u in range(nCOIs):\n",
    "    if isBigCOI[u] == 1:\n",
    "        print(\"splitting COI\",u,\"with pop\",COIpop[u])\n",
    "        for v in COItractList[u]:\n",
    "            unitPop.append(tractPop[v])\n",
    "            unitGeom.append(tractGeom[v])\n",
    "            unitTractList.append([v])\n",
    "            unitCP.append(tractCP[v])\n",
    "            unitOrigCOIno.append(u)\n",
    "    else:\n",
    "        unitPop.append(COIpop[u])\n",
    "        unitGeom.append(COIgeom[u])\n",
    "        unitTractList.append(COItractList[u].copy())\n",
    "        unitCP.append(COIgeom[u].centroid)\n",
    "        unitOrigCOIno.append(u)\n",
    "nUnits = len(unitPop)\n",
    "print(\"we now have\",nUnits,\"units from the original\",nCOIs,\"COIs\")\n",
    "print(\"total number of bg assignments plus skips are now\",len(skipList) + np.sum([len(unitTractList[u]) for u in range(nUnits)]) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "7bdc0d4e-5f7a-43a7-a1cb-26d915a4bbd8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "we found a total of 71 Units that were not rook-contiguous\n"
     ]
    }
   ],
   "source": [
    "isContigUnit = [False]*nUnits\n",
    "nonContigUnits = list()\n",
    "for c in range(nUnits):\n",
    "    isContigUnit[c] = isContiguous(unitTractList[c],bgNbrs)[0]\n",
    "    if not isContigUnit[c]:\n",
    "        nonContigUnits.append(c)\n",
    "print(\"we found a total of\",len(nonContigUnits),\"Units that were not rook-contiguous\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "4f581295-9cc0-4f5d-83e0-6215de0202db",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "check - all bgs assigned?\n",
      "9472 9472\n"
     ]
    }
   ],
   "source": [
    "print(\"check - all bgs assigned?\")\n",
    "print(len(tractPop), len(skipList) + np.sum([len(unitTractList[uu]) for uu in range(nUnits) ]) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "dd8ffbfb-9340-4f8e-ace5-a58312522c32",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "new for COI-Congrl - split out these units, like fragmented cities\n",
      "after splitting the 71 queen-adj units, we have 3211 units\n",
      "check - all bgs assigned?\n",
      "9472 9472\n"
     ]
    }
   ],
   "source": [
    "# SEE OH_615COIsnap99 for alt approach of maintaining queen adj except for crossovers\n",
    "print(\"new for COI-Congrl - split out these units, like fragmented cities\")\n",
    "for u in nonContigUnits:\n",
    "    nBGsAssigned, nBGsAvailable = 0, len(unitTractList[u])\n",
    "    contigList = getContigFromStarter(unitTractList[u][0],unitTractList[u],bgNbrs)\n",
    "    unitGeom[u] = tractGeom[contigList[0]]\n",
    "    for b in contigList:\n",
    "        unitGeom[u] = unitGeom[u].union(tractGeom[b])\n",
    "    unitPop[u] = np.sum([tractPop[b] for b in contigList])\n",
    "    unitCP[u] = unitGeom[u].centroid\n",
    "    remainList = list(set(unitTractList[u]).difference(set(contigList)) )\n",
    "    unitTractList[u] = contigList.copy()\n",
    "    nBGsAssigned += len(contigList)\n",
    "    while len(remainList) > 0:\n",
    "        contigList = getContigFromStarter(remainList[0],remainList,bgNbrs)\n",
    "        geo = tractGeom[contigList[0]]\n",
    "        for b in contigList:\n",
    "            geo = geo.union(tractGeom[b])\n",
    "        unitPop.append(np.sum([tractPop[b] for b in contigList]))\n",
    "        unitGeom.append(geo)\n",
    "        unitCP.append(geo.centroid)\n",
    "        unitTractList.append(contigList.copy())\n",
    "        nBGsAssigned += len(contigList)\n",
    "        remainList = list(set(remainList).difference(set(contigList)) )\n",
    "    if nBGsAssigned != nBGsAvailable:\n",
    "        print(\"oops, for unit\",u,\"only\",nBGsAssigned,\"were assigned out of\",nBGsAvailable)\n",
    "nUnits = len(unitPop)\n",
    "print(\"after splitting the\",len(nonContigUnits),\"queen-adj units, we have\",nUnits,\"units\")  \n",
    "print(\"check - all bgs assigned?\")\n",
    "print(len(tractPop), len(skipList) + np.sum([len(unitTractList[uu]) for uu in range(nUnits) ]) )\n",
    "        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "b9f7d2b5-5683-4ece-a4d7-4988aad8dbb6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Create the unit topology. First assign each bg's unit number (reverse of unitTractList)\n",
      "build unit nbr list based on adjacent bg's\n"
     ]
    }
   ],
   "source": [
    "print(\"Create the unit topology. First assign each bg's unit number (reverse of unitTractList)\")\n",
    "tractUnitNo = [-999 for bg in range(nTracts)]\n",
    "for u in range(nUnits):\n",
    "    for bg in unitTractList[u]:\n",
    "        tractUnitNo[bg] = u\n",
    "unitNbrSet = [set() for u in range(nUnits)]\n",
    "print(\"build unit nbr list based on adjacent bg's\")  #these are list-based, not geom-based\n",
    "for bg in range(nTracts):\n",
    "    u = tractUnitNo[bg]\n",
    "    for bb in bgNbrs[bg]:\n",
    "        uu = tractUnitNo[bb]\n",
    "        if uu != u  and uu >= 0:  #avoid assigning bg's relegated to unit -999\n",
    "            unitNbrSet[u].add(uu)\n",
    "unitNbrs = [list(unitNbrSet[u]) for u in range(nUnits)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "05609139-6975-42a4-96b1-b72b9ed7d5bd",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now let's find singles and small clusters surrounded by big units\n",
      "This is a more generalized surround operation\n",
      "checking for big surround for unit 0\n",
      "checking for big surround for unit 500\n",
      "checking for big surround for unit 1000\n",
      "checking for big surround for unit 1500\n",
      "checking for big surround for unit 2000\n",
      "checking for big surround for unit 2500\n",
      "checking for big surround for unit 3000\n",
      "I found a total of 93 surrounded units. nSurrounders = 61\n"
     ]
    }
   ],
   "source": [
    "print(\"Now let's find singles and small clusters surrounded by big units\")\n",
    "print(\"This is a more generalized surround operation\")\n",
    "surrounded, surrounders = list(), list()\n",
    "for u in range(nUnits):\n",
    "    if u%500 == 0:\n",
    "        print(\"checking for big surround for unit\",u)\n",
    "    nbrPops = [unitPop[uu] for uu in unitNbrs[u]]\n",
    "    bigNbrU = unitNbrs[u][nbrPops.index(np.max(nbrPops))]\n",
    "    loopNo, foundSet = 0, set(unitNbrs[u]).difference({bigNbrU})\n",
    "    while len(foundSet) < 10 and loopNo < 5:\n",
    "        loopNo +=1\n",
    "        for uu in foundSet:\n",
    "            foundSet = foundSet.union(set(unitNbrs[uu]).difference({bigNbrU}) )\n",
    "    if loopNo == 5:\n",
    "        surrounded.append(u)\n",
    "        surrounders.append(bigNbrU)\n",
    "print(\"I found a total of\",len(surrounded),\"surrounded units. nSurrounders =\",len(set(surrounders)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "e08ed07f-b2d5-4f3b-90ba-648d94ac2877",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "surrounded and faint surrounders\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for u in surrounded:\n",
    "    plotPoly(unitGeom[u])\n",
    "for u in surrounders:\n",
    "    plotPoly(unitGeom[u],0.1)\n",
    "print(\"surrounded and faint surrounders\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "4d708ece-cdf8-4de8-9079-70cade1bb117",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "now capture surrounds\n",
      "now update unitPops and CPs\n",
      "statePop, updated sum unitPops now 11799448 11799448.0\n",
      "total assigned BGs = 9466 6 vs 9472\n"
     ]
    }
   ],
   "source": [
    "print(\"now capture surrounds\")\n",
    "for i, u in enumerate(surrounded):\n",
    "    uu = surrounders[i]\n",
    "    unitNbrs[uu].remove(u)\n",
    "    unitNbrs[u] = list()\n",
    "    unitTractList[uu] += unitTractList[u]\n",
    "    for t in unitTractList[u]:\n",
    "        unitGeom[uu] = unitGeom[uu].union(tractGeom[t])\n",
    "        tractUnitNo[t] = uu\n",
    "    unitTractList[u] = list()\n",
    "print(\"now update unitPops and CPs\")\n",
    "unitPop = [np.sum([tractPop[b] for b in unitTractList[u] ]) for u in range(nUnits) ]\n",
    "unitCP = [unitGeom[u].centroid for u in range(nUnits) ]\n",
    "print(\"statePop, updated sum unitPops now\",np.sum(tractPop),np.sum(unitPop))\n",
    "print(\"total assigned BGs =\",np.sum([len(unitTractList[u]) for u in range(nUnits)]),len(skipList),\"vs\",nTracts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "07f4b7f3-6cbc-4aeb-93a2-80c8a9abc494",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now, cut out the surrounded units and transfer their pops.  We already fused the geoms and bg lists\n",
      "To be safe, we will reassign unit nbrs from bg topology in the next code block\n",
      "state pop = 11799448 = 11799448\n"
     ]
    }
   ],
   "source": [
    "print(\"Now, cut out the surrounded units and transfer their pops.  We already fused the geoms and bg lists\")\n",
    "print(\"To be safe, we will reassign unit nbrs from bg topology in the next code block\")\n",
    "oldPop, oldGeom, oldList = unitPop.copy(), unitGeom.copy(), [unitTractList[u].copy() for u in range(nUnits)]\n",
    "oldNbrs = [unitNbrs[u].copy() for u in range(nUnits) ]\n",
    "\n",
    "unitPop, unitGeom, unitTractList, oldUnitNo, nOldUnits = list(), list(), list(), list(), nUnits\n",
    "for u in range(nOldUnits):\n",
    "    if u not in surrounded:\n",
    "        oldUnitNo.append(u)\n",
    "        unitPop.append(np.sum([tractPop[t] for t in oldList[u] ]) )\n",
    "        unitGeom.append(oldGeom[u])\n",
    "        unitTractList.append(oldList[u].copy())\n",
    "nUnits = len(unitPop)\n",
    "unitNbrs = [list() for u in range(nUnits)]\n",
    "#for u in range(nUnits):   #to be safe, see next block for bg topology approach\n",
    "#    unitNbrs[u] = [oldUnitNo.index(uu) for uu in oldNbrs[oldUnitNo[u]] ]\n",
    "    \n",
    "tractUnitNo = [-999 for t in range(nTracts)]  #need to reset after surrounds\n",
    "for u in range(nUnits):\n",
    "    for bg in unitTractList[u]:\n",
    "        tractUnitNo[bg] = u\n",
    "print(\"state pop =\",np.sum(tractPop),\"=\",np.sum([np.sum([tractPop[b] for b in unitTractList[u] ]) for u in range(nUnits)]) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "d8ea0c58-fa3f-4eaf-a4e0-fc209d5433f7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "reassign unit nbrs based on bg topology\n",
      "build unit nbr list based on adjacent bg's\n"
     ]
    }
   ],
   "source": [
    "print(\"reassign unit nbrs based on bg topology\")\n",
    "unitNbrSet = [set() for u in range(nUnits)]\n",
    "print(\"build unit nbr list based on adjacent bg's\")  #these are list-based, not geom-based\n",
    "for bg in range(nTracts):\n",
    "    u = tractUnitNo[bg]\n",
    "    for bb in bgNbrs[bg]:\n",
    "        uu = tractUnitNo[bb]\n",
    "        if uu != u  and uu >= 0:  #avoid assigning bg's relegated to unit -999\n",
    "            unitNbrSet[u].add(uu)\n",
    "unitNbrs = [list(unitNbrSet[u]) for u in range(nUnits)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "85596af1-4676-4a17-ab31-1e6a7f8edaaa",
   "metadata": {},
   "outputs": [],
   "source": [
    "unitCP = [unitGeom[u].centroid for u in range(nUnits)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "fb97611f-2fe5-4a8f-8478-4c6955689668",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "defining border counties\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "We will use previously defined and read-in border bgs\n"
     ]
    }
   ],
   "source": [
    "print(\"defining border counties\")\n",
    "Kelley, Knbrs = 5879, [5870, 5871]  #in case we used previously saved bg topology vs. defining in this run\n",
    "borderCounties = list()\n",
    "for c in range(nCounties):\n",
    "    if countyGeom[c].intersects(mainMAP.exterior):\n",
    "        borderCounties.append(c)\n",
    "        plotPoly(countyGeom[c])\n",
    "plt.show()\n",
    "usePrevious = True\n",
    "if usePrevious:\n",
    "    print(\"We will use previously defined and read-in border bgs\")\n",
    "else:\n",
    "    print(\"Now we determine and plot the border bgs\")\n",
    "    borderBGs = list()\n",
    "    for c in borderCounties:\n",
    "        for bg in countyTractList[c]:\n",
    "            if isRookAdj(tractGeom[bg],mainMAP.exterior) or bg == Kelley:\n",
    "                borderBGs.append(bg)\n",
    "                plotPoly(tractGeom[bg])\n",
    "    plt.show()\n",
    "    isBorderBG = [0]*nTracts\n",
    "    for bg in borderBGs:\n",
    "        isBorderBG[bg] = 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "8bcc5cfe-d24f-45bf-b006-778d3147e509",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "check -- are coastal units excluded?  Do most bgs have 2+ neighbors?\n",
      "46 in county 37 has only neigborlist [54]\n",
      "520 in county 63 has only neigborlist [522]\n",
      "1098 in county 16 has only neigborlist [1089]\n",
      "1420 in county 53 has only neigborlist [7933]\n",
      "2511 in county 25 has only neigborlist [2450]\n",
      "2985 in county 80 has only neigborlist [2745]\n",
      "4101 in county 79 has only neigborlist [4102]\n",
      "4921 in county 7 has only neigborlist [4947]\n",
      "6277 in county 66 has only neigborlist [6718]\n",
      "6329 in county 49 has only neigborlist [1150]\n",
      "6369 in county 28 has only neigborlist [3717]\n",
      "6601 in county 28 has only neigborlist [6424]\n",
      "7275 in county 35 has only neigborlist [7286]\n",
      "7420 in county 23 has only neigborlist [7413]\n",
      "7696 in county 24 has only neigborlist [1384]\n",
      "8531 in county 85 has only neigborlist [8914]\n",
      "8694 in county 19 has only neigborlist [6949]\n",
      "9025 in county 28 has only neigborlist [6702]\n",
      "9277 in county 24 has only neigborlist [3069]\n"
     ]
    }
   ],
   "source": [
    "print(\"check -- are coastal units excluded?  Do most bgs have 2+ neighbors?\")\n",
    "for b in range(nTracts):\n",
    "    if b in skipList:\n",
    "        if len(bgNbrs[b]) > 0:\n",
    "            print(\"warning: skipped bg\",b,\"has some bg neighbors\")\n",
    "    else:\n",
    "        if len(set(skipList).intersection(set(bgNbrs[b])) ) > 0:\n",
    "            print(\"warning. b\",b,\"has skipList neighbors\")\n",
    "        if len(bgNbrs[b]) < 2:\n",
    "            print(b,\"in county\",countyNo[b],\"has only neigborlist\",bgNbrs[b])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "3eeda00e-460c-4ca0-9d79-bbf89e24c4fb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "how contig is the set of border BGs?\n",
      "the contig list has length 367 vs total 367\n",
      "border BG 5879 has < 2 border neighbors\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"how contig is the set of border BGs?\")\n",
    "contigList = getContigFromStarter(borderBGs[0],borderBGs,bgNbrs)\n",
    "print(\"the contig list has length\",len(contigList),\"vs total\",len(borderBGs))\n",
    "for b in borderBGs:\n",
    "    if len(set(bgNbrs[b]).intersection(set(borderBGs))) < 2:\n",
    "        print(\"border BG\",b,\"has < 2 border neighbors\")\n",
    "        plotPoly(tractGeom[b])\n",
    "        plotCenter(b,tractGeom[b])\n",
    "        for bb in bgNbrs[b]:\n",
    "            plotPoly(tractGeom[bb],0.3)\n",
    "            if bb in borderBGs:\n",
    "                plotCenter(\"border\"+str(bb),tractGeom[bb])\n",
    "            else:\n",
    "                plotCenter(\"nonb\"+str(bb),tractGeom[bb])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "09b51578-0314-4c13-a1f3-196ca8f55bc1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "creating some corner connectivity\n"
     ]
    }
   ],
   "source": [
    "#THIS BLOCK ONLY NECESSARY IF WE DID NOT READ IN THE modBGtopology\n",
    "#print(\"creating some corner connectivity\")\n",
    "#bgNbrs[7664].append(6683)\n",
    "#bgNbrs[6683].append(7664) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "a6a8cdd3-55e2-4f24-a63a-e0efe0a9fb0a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Border bg integrity check: number of border BGs = 367\n",
      "border is discontig if we skip bg 5870\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"Border bg integrity check: number of border BGs =\",len(borderBGs))\n",
    "nLoop = 0\n",
    "for b in borderBGs:\n",
    "    isUnbroken, smallPieceList = isContiguous(list(set(borderBGs).difference({b})),bgNbrs)\n",
    "    if not isUnbroken:\n",
    "        nLoop +=1\n",
    "        print(\"border is discontig if we skip bg\",b)\n",
    "        if nLoop < 5:  #avoid excessive printing\n",
    "            for bb in smallPieceList:\n",
    "                plotPoly(tractGeom[bb],0.2)\n",
    "                plotCenter(\"n\"+str(bb),tractGeom[bb])\n",
    "            plotCenter(b,tractGeom[b])\n",
    "            plotPoly(tractGeom[b],1)\n",
    "            plt.show()  #below is OK - Kelleys Island is part of a larger unit\n",
    "borderBGset = set(borderBGs) "
   ]
  },
  {
   "cell_type": "raw",
   "id": "42d9812d-9191-434a-8064-9b95ea518bf7",
   "metadata": {},
   "source": [
    "date = \"17Nov24\"  #THIS WAS DONE IN OH_615COIsnap99, so do not repeat here\n",
    "isBorderBG = [0]*nTracts\n",
    "for b in borderBGs:\n",
    "    isBorderBG[b] = 1\n",
    "tractCPx, tractCPy = [tractCP[t].x for t in range(nTracts)], [tractCP[t].y for t in range(nTracts)]\n",
    "print(\"lets write the modified blockgroup topology to a file\")\n",
    "bgNo = [b for b in range(nTracts)]\n",
    "bgDF = pd.DataFrame( {\"bgNo\":bgNo,\"centroid x\":tractCPx,\"centroid y\":tractCPy,\"bgPop\":tractPop,\"bgNbrs\":bgNbrs,\n",
    "                     \"countyNo\":countyNo,\"isBorderBG\":isBorderBG} )\n",
    "outname = STATE+str(nDistricts)+\"mod_bgTopologies_\"+date+\".csv\" \n",
    "outpath = \"state_map_files/\"+outname\n",
    "bgDF.to_csv(outpath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e934066e-a4d6-4279-afad-1ac87da4b4c2",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "raw",
   "id": "659c8b5d-3869-44aa-9b63-df01fcc10625",
   "metadata": {},
   "source": [
    "print(\"Alternatively we read in the bg topology\")  #this may be after an initial surround op\n",
    "infile = \"./state_map_files/OH99mod_bgTopologies_17Nov24.csv\"\n",
    "bgDF = pd.read_csv(infile)\n",
    "tractCPx = bgDF[\"centroid x\"]\n",
    "tractCPy = bgDF[\"centroid y\"]\n",
    "tractPop = bgDF[\"bgPop\"]\n",
    "bgNbrList = bgDF[\"bgNbrs\"]\n",
    "countyNo = bgDF[\"countyNo\"]\n",
    "isBorderBG = bgDF[\"isBorderBG\"]\n",
    "borderBGs = list()\n",
    "for b in range(len(isBorderBG)):\n",
    "    if isBorderBG[b] == 1:\n",
    "        borderBGs.append(b)\n",
    "nTracts = len(tractPop)\n",
    "statePop = np.sum(tractPop)\n",
    "#bgNbrs = bgNbrList.copy()\n",
    "bgNbrs = [ast.literal_eval(bgNbrList[t]) for t in range(nTracts) ]\n",
    "print(\"I read in the blockgroup topology; there are\",nTracts,\"blockgroups and state pop of\",statePop)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 246,
   "id": "2c6b45be-0113-4364-bd2c-30c4546479a3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "here is a histogram of number of unit neighbors\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "nUnitNbrs = [len(unitNbrs[u]) for u in range(nUnits)]\n",
    "print(\"here is a histogram of number of unit neighbors\")\n",
    "plt.hist(nUnitNbrs,bins=[0,1,2,3,5,7,10,20,30,40,80])\n",
    "plt.axvline(0.5,ls=\"--\")\n",
    "plt.axvline(1.5,ls=\"--\")\n",
    "plt.show()\n",
    "for u in range(nUnits):\n",
    "    if nUnitNbrs[u] == 1:\n",
    "        print(\"unit\",u,\"has only neighbor\",unitNbrs[u][0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 247,
   "id": "e59b40c6-dac2-4165-9fe1-79c374b2e1c0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "state pop = 11799448 = 11799448\n"
     ]
    }
   ],
   "source": [
    "print(\"state pop =\",np.sum(tractPop),\"=\",np.sum([np.sum([tractPop[b] for b in unitTractList[u] ]) for u in range(nUnits)]) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 248,
   "id": "5e97fc0b-1757-49c4-a723-7f594bb264af",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "sum of unit areas = 11.460253084569995 vs map area 11.46025308457\n"
     ]
    }
   ],
   "source": [
    "print(\"sum of unit areas =\",np.sum([unitGeom[u].area for u in range(nUnits)]),\"vs map area\",mainMAP.area + tractArea[Kelley])\n",
    "#main excludes Kelleys Island"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 249,
   "id": "1cb139b5-d99d-4693-a8ef-e9173fb475ef",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "state nTracts = 9472 = 9466 + 6\n"
     ]
    }
   ],
   "source": [
    "print(\"state nTracts =\",nTracts,\"=\",np.sum([len( unitTractList[u] ) for u in range(nUnits)]) ,\"+\",len(skipList) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 250,
   "id": "930e18b7-dc45-456a-83da-6682553baff9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "spot check of new unit nbr lists ...\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"spot check of new unit nbr lists ...\")\n",
    "for u in [5, nUnits -1]:\n",
    "    plotPoly(unitGeom[u])\n",
    "    for uu in unitNbrs[u]:\n",
    "        plotPoly(unitGeom[uu],0.1)\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "6684a743-8342-46ca-8c92-054ea34dc6d2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "identify the border units.  Numbered units have zero nonborder neighbors; will be surrounded next block\n",
      "'pop' shows pop/aDP for pop/aDP > 0.5 in a border unit\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"identify the border units.  Numbered units have zero nonborder neighbors; will be surrounded next block\")\n",
    "print(\"'pop' shows pop/aDP for pop/aDP > 0.5 in a border unit\")\n",
    "isBorder = [0]*nUnits\n",
    "borderSet = set()\n",
    "for b in borderBGs:\n",
    "    u = tractUnitNo[b]\n",
    "    borderSet.add(u)\n",
    "    isBorder[u] = 1\n",
    "borderUnits = list(borderSet)\n",
    "surroundedBorderUnits = list()\n",
    "for u in borderUnits:\n",
    "    plotPoly(unitGeom[u])\n",
    "    if len(set(unitNbrs[u]).difference(set(borderUnits)) ) == 0:\n",
    "        plotCenter(u,unitGeom[u],9)\n",
    "        surroundedBorderUnits.append(u)\n",
    "    if unitPop[u] > 0.5 * aDP:\n",
    "        plotCenter(\"pop\"+str(r3(unitPop[u]/aDP)),unitGeom[u],8)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "d8ac804b-fedc-457c-bf73-2eb0169b4077",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "we will collapse unit 3101 into unit 2929\n",
      "we will collapse unit 2633 into unit 2641\n",
      "we will collapse unit 1614 into unit 1617\n",
      "we will collapse unit 1620 into unit 1617\n",
      "we will collapse unit 1621 into unit 1491\n",
      "we will collapse unit 1129 into unit 1130\n",
      "we will collapse unit 669 into unit 925\n",
      "we will collapse unit 2207 into unit 2208\n",
      "we will collapse unit 678 into unit 2926\n",
      "we will collapse unit 2226 into unit 2641\n",
      "we will collapse unit 254 into unit 386\n",
      "we will collapse unit 255 into unit 386\n",
      "we will collapse unit 1829 into unit 2896\n",
      "we will collapse unit 1323 into unit 1491\n",
      "we will collapse unit 376 into unit 555\n",
      "we will collapse unit 2947 into unit 626\n",
      "we will collapse unit 919 into unit 925\n",
      "we will collapse unit 2000 into unit 2692\n",
      "we will collapse unit 500 into unit 536\n"
     ]
    }
   ],
   "source": [
    "surrounderBorderUnits = list()\n",
    "for u in surroundedBorderUnits:\n",
    "    candidates = list()\n",
    "    for uu in set(unitNbrs[u]).difference(set(surroundedBorderUnits)):\n",
    "        candidates.append(uu)\n",
    "    uuDists = [unitCP[u].distance(unitCP[uu]) for uu in candidates]\n",
    "    uuu = candidates[uuDists.index(np.min(uuDists)) ]\n",
    "    print(\"we will collapse unit\",u,\"into unit\",uuu)\n",
    "    surrounderBorderUnits.append(uuu)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "45dc8100-0e51-47e1-9d17-9cb204e7fed2",
   "metadata": {},
   "outputs": [],
   "source": [
    "for u in surrounderBorderUnits:\n",
    "    if u in surroundedBorderUnits:\n",
    "        print(\"uhoh, we named\",u,\"as a surrounder but it was surrounded\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "0eb4bffe-b45e-4a02-a050-b9191c45e897",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "absorbing surrounded border units ...\n"
     ]
    }
   ],
   "source": [
    "oldList = [unitTractList[u].copy() for u in range(nUnits)] #safekeeping\n",
    "print(\"absorbing surrounded border units ...\")\n",
    "for u in range(nUnits):\n",
    "    if u in surroundedBorderUnits:\n",
    "        uu = surrounderBorderUnits[surroundedBorderUnits.index(u)]\n",
    "        oldList[uu] += oldList[u]\n",
    "        oldList[u] = list()\n",
    "unitTractList, unitPop = list(), list()\n",
    "for u in range(nUnits):\n",
    "    if u not in surroundedBorderUnits:\n",
    "        unitTractList.append(oldList[u])\n",
    "        unitPop.append(np.sum([tractPop[b] for b in oldList[u] ]))\n",
    "nUnits = len(unitPop)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "48cf21a6-325d-4b95-b094-9b3fe946c7b0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "and updating the reverse bg-unit assignments ...\n",
      "lists and pops updated.  Now the topology for remaining units 3099\n",
      "build unit nbr list based on adjacent bg's\n",
      "now rebuilding unit geometries ...\n",
      "rebuilding geom for unit 0\n",
      "rebuilding geom for unit 500\n",
      "rebuilding geom for unit 1000\n",
      "rebuilding geom for unit 1500\n",
      "rebuilding geom for unit 2000\n",
      "rebuilding geom for unit 2500\n",
      "rebuilding geom for unit 3000\n",
      "we captured 19 surrounded units\n",
      "state pop = 11799448 = 11799448\n"
     ]
    }
   ],
   "source": [
    "print(\"and updating the reverse bg-unit assignments ...\")\n",
    "for u in range(nUnits):\n",
    "    for b in unitTractList[u]:\n",
    "        tractUnitNo[b] = u\n",
    "\n",
    "print(\"lists and pops updated.  Now the topology for remaining units\",nUnits)\n",
    "unitNbrSet = [set() for u in range(nUnits)]\n",
    "print(\"build unit nbr list based on adjacent bg's\")  #these are list-based, not geom-based\n",
    "for bg in range(nTracts):\n",
    "    u = tractUnitNo[bg]\n",
    "    for bb in bgNbrs[bg]:\n",
    "        uu = tractUnitNo[bb]\n",
    "        if uu != u  and uu >= 0:  #avoid assigning bg's relegated to unit -999\n",
    "            unitNbrSet[u].add(uu)\n",
    "unitNbrs = [list(unitNbrSet[u]) for u in range(nUnits)]\n",
    "print(\"now rebuilding unit geometries ...\")\n",
    "unitGeom = list()\n",
    "for u in range(nUnits):\n",
    "    if u%500 == 0:\n",
    "        print(\"rebuilding geom for unit\",u)\n",
    "    geo = tractGeom[unitTractList[u][0]]\n",
    "    for b in unitTractList[u]:\n",
    "        if b != unitTractList[u][0]:\n",
    "            geo = geo.union(tractGeom[b])\n",
    "    unitGeom.append(geo)\n",
    "print(\"we captured\",len(surroundedBorderUnits),\"surrounded units\")\n",
    "print(\"state pop =\",np.sum(tractPop),\"=\",np.sum([np.sum([tractPop[b] for b in unitTractList[u] ]) for u in range(nUnits)]) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "48213b6e-2e5d-426a-a6b9-1be51b5cd438",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "state bgs = 9472 = 9472\n"
     ]
    }
   ],
   "source": [
    "print(\"state bgs =\",len(tractPop),\"=\",np.sum([np.sum([1 for b in unitTractList[u] ]) for u in range(nUnits)])  + len(skipList) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "b4b7cab1-36b7-4885-834d-2a8e0a2c87dd",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "additional integrity checks -- bg's assigned to non-units\n"
     ]
    }
   ],
   "source": [
    "print(\"additional integrity checks -- bg's assigned to non-units\")\n",
    "for u in range(nUnits):\n",
    "    for bg in unitTractList[u]:\n",
    "        tractUnitNo[bg] = u\n",
    "        if tractUnitNo[bg] < 0:\n",
    "            print(\"based on tract unit list, bg\",bg,\"was assigned to non-unit\",u)\n",
    "for bg in range(nTracts):\n",
    "    if bg not in skipList and tractUnitNo[bg] < 0:\n",
    "        print(\"based on bg list, bg\",bg,\"was assigned to non-unit\",tractUnitNo[bg])\n",
    "        for u in range(nUnits):\n",
    "            if bg in unitTractList[u]:\n",
    "                tractUnitNo[bg] = 0\n",
    "                print(\" ... but I assigned bg\",bg,\"to unit\",u)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "b9993ece-c7c6-4dc6-8ff7-b0a3a4a3dac1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "do we have discontig units??\n"
     ]
    }
   ],
   "source": [
    "print(\"do we have discontig units??\")\n",
    "for u in range(nUnits):\n",
    "    if len(unitTractList[u]) > 1:\n",
    "        if not isContiguous(unitTractList[u],bgNbrs):\n",
    "            print(u,\"is not contiguous\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "730fa1c1-edf4-4718-99a6-8fdad2cf42b6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Re-identify the border units.  Numbered units have no nonborder neighbors; would need to triage these again\n",
      "our new set of surroundedBorderUnits is []\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"Re-identify the border units.  Numbered units have no nonborder neighbors; would need to triage these again\")\n",
    "isBorder = [0]*nUnits\n",
    "borderSet = set()\n",
    "for b in borderBGs:\n",
    "    u = tractUnitNo[b]\n",
    "    borderSet.add(u)\n",
    "    isBorder[u] = 1\n",
    "borderUnits = list(borderSet)\n",
    "surroundedBorderUnits2 = list()\n",
    "for u in borderUnits:\n",
    "    plotPoly(unitGeom[u])\n",
    "    if len(set(unitNbrs[u]).difference(set(borderUnits)) ) == 0:\n",
    "        plotCenter(u,unitGeom[u],9)\n",
    "        surroundedBorderUnits2.append(u)\n",
    "print(\"our new set of surroundedBorderUnits is\",surroundedBorderUnits2)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "5012ff9c-b3e4-4196-8007-cf603475a877",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "number of border units = 157\n"
     ]
    }
   ],
   "source": [
    "print(\"number of border units =\",len(borderUnits))\n",
    "nLoop = 0\n",
    "for u in borderUnits:\n",
    "    isUnbroken, smallPieceList = isContiguous(list(set(borderUnits).difference({u})),unitNbrs)\n",
    "    if not isUnbroken:\n",
    "        nLoop +=1\n",
    "        print(\"border is discontig if we skip\",u)\n",
    "        if nLoop < 5:  #avoid excessive printing\n",
    "            for uu in smallPieceList:\n",
    "                plotPoly(unitGeom[uu],0.2)\n",
    "                plotCenter(\"n\"+str(uu),unitGeom[uu])\n",
    "            plotCenter(u,unitGeom[u])\n",
    "            plotPoly(unitGeom[u],1)\n",
    "            plt.show()\n",
    "borderSet = set(borderUnits)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "e0545c19-3336-4bad-9acf-5eb90106ff6c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Here are the unsplittable municipalities, between 35pct and 101% of a Congressional district\n",
      "636 373085 with first bg in county 46\n",
      "1651 572606 with first bg in county 37\n",
      "and which ones are 0.2 - 0.35 aDP?\n"
     ]
    }
   ],
   "source": [
    "unitPop = [ np.sum([tractPop[b] for b in unitTractList[u] ]) for u in range(nUnits) ]\n",
    "unsplittableUnits = list()\n",
    "cantSplit = [0]*nUnits\n",
    "print(\"Here are the unsplittable municipalities, between 35pct and 101% of a Congressional district\")\n",
    "for u in range(nUnits):\n",
    "    if unitPop[u] < 1.01*avgDistrictPop and unitPop[u] > 0.35 * avgDistrictPop:\n",
    "        unsplittableUnits.append(u)\n",
    "        cantSplit[u] = 1\n",
    "        print(u, r3(unitPop[u]),\"with first bg in county\",countyNo[unitTractList[u][0]])\n",
    "print(\"and which ones are 0.2 - 0.35 aDP?\")\n",
    "for u in range(nUnits):\n",
    "    if unitPop[u] < 0.2*avgDistrictPop and unitPop[u] > 0.35 * avgDistrictPop:\n",
    "        print(\"   \",u, r3(unitPop[u]),\"with first bg in county\",countyNo[unitTractList[u][0]] )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "7254078e-b271-4790-b2f8-9820720e2f08",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "the set of whole units (0.99 - 1.01 aDP) is set() with pops/aDP of []\n"
     ]
    }
   ],
   "source": [
    "wholeSet = set()\n",
    "for u in range(nUnits):\n",
    "    if unitPop[u] > 0.99 * aDP and unitPop[u] < 1.01 * aDP:\n",
    "        wholeSet.add(u)\n",
    "print(\"the set of whole units (0.99 - 1.01 aDP) is\",wholeSet,\"with pops/aDP of\",[r3(unitPop[u]/aDP) for u in wholeSet])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "9971e41c-0c39-4bb2-9916-b20a4075f9a8",
   "metadata": {},
   "outputs": [],
   "source": [
    "unitCP = [unitGeom[u].centroid for u in range(nUnits) ]\n",
    "unitCPx = [unitCP[u].x for u in range(nUnits) ]\n",
    "unitCPy = [unitCP[u].y for u in range(nUnits) ]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 263,
   "id": "3c950093-cef8-43ca-ac68-6451cb06e858",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "write the COI-Congr unit topology to a file ...\n"
     ]
    }
   ],
   "source": [
    "print(\"write the COI-Congr unit topology to a file ...\")\n",
    "date = \"01Dec\"\n",
    "nUnits = len(unitPop)\n",
    "unitNo = [u for u in range(nUnits)]\n",
    "onBorder = [0 for u in range(nUnits)]\n",
    "unitCountyNo = [countyNo[unitTractList[u][0]] for u in range(nUnits)]  #this may be off for county-straddling units\n",
    "\n",
    "for u in borderUnits:\n",
    "    onBorder[u] = 1\n",
    "nbrDF = pd.DataFrame( {\"unitNo\":unitNo,\"centroid x\":unitCPx,\"centroid y\":unitCPy,\"unitPop\":unitPop,\"onBorder\":onBorder,\n",
    "                       \"cantSplit\":cantSplit,\"unitNbrs\":unitNbrs, \"unitCountyNo\":unitCountyNo,\"unitTractList\":unitTractList} )\n",
    "outname = STATE+str(nDistricts)+\"COI615-unitTopologiesBG_\"+date+\".csv\" \n",
    "outpath = \"state_map_files/\"+outname\n",
    "nbrDF.to_csv(outpath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "6007df08-67a8-42f3-b65b-145aeac2e050",
   "metadata": {},
   "outputs": [],
   "source": [
    "for u in range(nUnits):\n",
    "    if unitPop[u] < 10:\n",
    "        print(u,\"has\",len(unitTractList[u]),\"bg's in it.  Total unit pop is \",unitPop[u])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "0d963fd9-f506-4309-883a-6c8876af81c2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Pull in the any-split Home Districts.  These were based on VTDs, not blockgroups ...\n",
      "Now convert (approximately) to full VTD lists. We didn't store the VTDfrag lists, so use binary in-out if frac > 0.5\n"
     ]
    }
   ],
   "source": [
    "\n",
    "print(\"Pull in the any-split Home Districts.  These were based on VTDs, not blockgroups ...\")\n",
    "infile = \"./2024state_HD_output/OH8941VRApatchedVTDs.csv\"\n",
    "HDdf = pd.read_csv(infile)\n",
    "HDvtdListString, partialString, fracString = HDdf[\"HDvtdList\"], HDdf[\"partials\"],HDdf[\"HDvtdFrac\"]\n",
    "nHDs = len(HDvtdListString)\n",
    "HDCPx, HDCPy, HDwt = HDdf[\"centroid x\"],HDdf[\"centroid y\"], HDdf[\"HDweight\"]\n",
    "HDvTruePop = HDdf[\"HDvPop\"]\n",
    "HDCP = [Point(HDCPx[v], HDCPy[v]) for v in range(nHDs)]\n",
    "hdCP = HDCP.copy() #nomenclature\n",
    "HDvtdList = [ast.literal_eval(HDvtdListString[h]) for h in range(nHDs)]\n",
    "HDpartials = [ast.literal_eval(partialString[h]) for h in range(nHDs)]\n",
    "HDvtdFrac = [ast.literal_eval(fracString[h]) for h in range(nHDs)]\n",
    "print(\"Now convert (approximately) to full VTD lists. We didn't store the VTDfrag lists, so use binary in-out if frac > 0.5\")\n",
    "for h in range(nHDs):\n",
    "    for i, frac in enumerate(HDvtdFrac[h]):\n",
    "        if frac >= 0.5:\n",
    "            HDvtdList[h].append(HDpartials[h][i])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "400dac53-1036-4ff3-ae0c-bca26de36417",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now read in the vtd geometry file, to later enable HD geoms for later spatial snapping\n"
     ]
    }
   ],
   "source": [
    "print(\"Now read in the vtd geometry file, to later enable HD geoms for later spatial snapping\")\n",
    "vtdPopFile = gpd.read_file(\"state_map_files/oh_pl2020_vtd.dbf\")\n",
    "vtdGeom = vtdPopFile['geometry']\n",
    "vtdPop = vtdPopFile['P0010001']\n",
    "nVTDs = len(vtdGeom)\n",
    "vtdArea = [vtdGeom[v].area for v in range(nVTDs)]\n",
    "vtdCP = [vtdGeom[v].centroid for v in range(nVTDs)]\n",
    "vtdCN = vtdPopFile['COUNTYFP20']\n",
    "vtdCountyNo = list()\n",
    "for v in range(nVTDs):\n",
    "    vtdCountyNo.append( int((int(vtdCN[v]) - 1)/2) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "10d0c6ee-a37c-4ee4-b644-78f2d887b3af",
   "metadata": {},
   "outputs": [],
   "source": [
    "isSkippedVTD = [0] *nVTDs  #this will house a temporary list of tracts for manipulation\n",
    "skippedVTDs = [8197, 4634, 3730, 4458, 840, 2974, 1008]\n",
    "for v in skippedVTDs:\n",
    "    isSkippedVTD[v] = 1\n",
    "countyVTDlist = [list() for c in range(nCounties)]\n",
    "for v in range(nVTDs):\n",
    "    if v not in skippedVTDs:\n",
    "        countyVTDlist[vtdCountyNo[v]].append(v)"
   ]
  },
  {
   "cell_type": "raw",
   "id": "e92b1969-9bc6-4de9-9f7f-b26068221f50",
   "metadata": {},
   "source": [
    "#######SKIP THIS option A BLOCK IF WE WILL READ IN PREVIOUSLY VTD --> BG MAPPED HD'S\n",
    "#HDvtdGeom = list()\n",
    "print(\"now we snap -- spatially determine HDgeom - blockgroup capture --> unitFracs\")\n",
    "popHDlist = list()\n",
    "startTime = time.time()\n",
    "unitFrac = [[0.]*nUnits for h in range(nHDs)]\n",
    "HDbgList = [list() for h in range(nHDs)]\n",
    "for h in range(nHDs):\n",
    "    if h%400 == 0:\n",
    "        print(\"building temporary HDvtdGeom for HD\",h,\"time is now\",int(time.time() - startTime))\n",
    "    if len(HDvtdList[h]) == 0:\n",
    "        #HDvtdGeom.append(dummyPoly)  #too much memory to store individually.\n",
    "        pass\n",
    "    else:\n",
    "        popHDlist.append(h)\n",
    "        #geo = vtdGeom[ HDvtdList[h][0] ]\n",
    "        HDcountyVTDs = [list() for c in range(nCounties)]\n",
    "        HDcountyGeo = [dummyPoly]*nCounties\n",
    "        capturedCounty = [0]*nCounties\n",
    "        for v in HDvtdList[h]:\n",
    "            c = vtdCountyNo[v]\n",
    "            HDcountyVTDs[c].append(v)\n",
    "        for c in range(nCounties):\n",
    "            if len(HDcountyVTDs[c]) > 0:  #some of county was HD-captured\n",
    "                if len(HDcountyVTDs[c]) >= 0.98 * len(countyVTDlist[c]) : #the HD essentially captured the county\n",
    "                    capturedCounty[c] = 1\n",
    "                    HDcountyGeo[c] = countyGeom[c]\n",
    "                else:\n",
    "                    HDcountyGeo[c] = vtdGeom[HDcountyVTDs[c][0]]\n",
    "                    for v in HDcountyVTDs[c]:\n",
    "                        HDcountyGeo[c] = HDcountyGeo[c].union(vtdGeom[v])\n",
    "\n",
    "        bList = list()\n",
    "        for c in range(nCounties):\n",
    "            if HDcountyGeo[c] != dummyPoly : #geo.intersects(countyGeom[c]):\n",
    "                if capturedCounty[c] == 1: #HDcountyGeo[c].contains(countyGeom[c]): #geo.contains(countyGeom[c]):\n",
    "                    for b in countyTractList[c]:\n",
    "                        bList.append(b)\n",
    "                else:\n",
    "                    for b in countyTractList[c]:\n",
    "                        if HDcountyGeo[c].contains(tractCP[b]): #geo.contains(tractCP[b]):\n",
    "                            bList.append(b)\n",
    "        HDbgList[h] = bList.copy()\n",
    "        for b in bList:\n",
    "            if b not in skipList and tractUnitNo[b] >= 0: #protect against unassigned 0-pop blockgroups\n",
    "                u = tractUnitNo[b]\n",
    "                if unitPop[tractUnitNo[b]] == 0:                       \n",
    "                    unitFrac[h][u] = 1.\n",
    "                else:\n",
    "                    unitFrac[h][u] += tractPop[b]/unitPop[u]\n",
    "        "
   ]
  },
  {
   "cell_type": "raw",
   "id": "64cd3a98-a327-458f-bb59-1f29f962eef3",
   "metadata": {},
   "source": [
    "print(\"save this HDvtdList --> HDbgList to a file\") #useful block for COI615=COI1850\n",
    "tList = [t for t in range(nHDs)]\n",
    "outDF = pd.DataFrame( {\"HD\":tList,\"HDweight\":HDwt,\"HDbgList\":HDbgList} )\n",
    "outname = STATE+str(int(nHDs))+\"VRAbgLists.csv\"\n",
    "outpath = \"2024state_HD_output/\"+outname\n",
    "outDF.to_csv(outpath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f7353c13-18ea-464d-92b9-51657194fa1e",
   "metadata": {},
   "outputs": [],
   "source": [
    "#using HD geo approach, 600 HDs in 100 minutes.  List approach: about 4000 HDs / 100 min"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "5b6689ce-78c5-4837-bb46-5f9e2598178b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "reading in the previously stored HD bg lists\n",
      "of the 8941 total HDs, 8934 are non-empty\n"
     ]
    }
   ],
   "source": [
    "print(\"reading in the previously stored HD bg lists\")\n",
    "listDF = pd.read_csv(\"./2024state_HD_output/OH8941VRAbgLists.csv\")\n",
    "bgListString = listDF[\"HDbgList\"]\n",
    "HDwt = listDF[\"HDweight\"]\n",
    "HDweight = HDwt.copy()\n",
    "nHDs = len(bgListString)\n",
    "HDbgList = [ast.literal_eval(bgListString[h]) for h in range(nHDs) ]\n",
    "popHDlist = list()\n",
    "for h in range(nHDs):\n",
    "    if len(HDbgList[h]) > 0:\n",
    "        popHDlist.append(h)\n",
    "print(\"of the\",nHDs,\"total HDs,\",len(popHDlist),\"are non-empty\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "eb8f4b36-22e8-4b9b-a493-23e7d66d9755",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist([len(HDbgList[h]) for h in popHDlist])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "abb8ff04-a3e4-4fff-8fb9-15613a165c7a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "continuing option b: convert HDbgLists to unit frac usages\n"
     ]
    }
   ],
   "source": [
    "print(\"continuing option b: convert HDbgLists to unit frac usages\")\n",
    "unitFrac = [[0.]*nUnits for h in range(nHDs)]\n",
    "for h in popHDlist:\n",
    "    if h%1000 == 0:\n",
    "        print(\"converting bg list to unit fractions for HD\",h)\n",
    "    bList = HDbgList[h].copy()\n",
    "    for b in bList:\n",
    "        if b not in skipList and tractUnitNo[b] >= 0: #protect against unassigned 0-pop blockgroups\n",
    "            u = tractUnitNo[b]\n",
    "            if unitPop[tractUnitNo[b]] == 0:                       \n",
    "                unitFrac[h][u] = 1.\n",
    "            else:\n",
    "                unitFrac[h][u] += tractPop[b]/unitPop[u]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "1fbef9d8-35f8-49cf-bb3e-6d6acf517033",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "8941 786629.8666666667 9472 3099\n",
      "35\n"
     ]
    }
   ],
   "source": [
    "print(nHDs, aDP, nTracts, nUnits)\n",
    "print(np.min(unitPop))\n",
    "countyUnitList = [list() for c in range(nCounties)]\n",
    "unitCountyNo = [countyNo[unitTractList[u][0]] for u in range(nUnits)]  #this may be off for county-straddling units\n",
    "for u in range(nUnits):\n",
    "    countyUnitList[unitCountyNo[u]].append(u)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "6d5085d1-1dd0-465c-98f4-d4769f5eadde",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "In this block, define each HDcp's home unit. Next block will then build unit-based HDs out from home muni...\n",
      "since units are blockgroup based, we assign HD centerpoints to the unit that contains it\n",
      "determining homeU for HD 0 time is now 0\n",
      "determining homeU for HD 1000 time is now 30\n",
      "determining homeU for HD 2000 time is now 42\n",
      "determining homeU for HD 3000 time is now 61\n",
      "determining homeU for HD 4000 time is now 71\n",
      "determining homeU for HD 5000 time is now 85\n",
      "determining homeU for HD 6000 time is now 102\n",
      "determining homeU for HD 7000 time is now 117\n",
      "determining homeU for HD 8000 time is now 129\n"
     ]
    }
   ],
   "source": [
    "print(\"In this block, define each HDcp's home unit. Next block will then build unit-based HDs out from home muni...\")\n",
    "minSnapFrac, minEligFrac = 0.667, 0.1 #we auto-add contig munis at least this full in HDvtdList\n",
    "homeU, HDvPop, HDunitList = [-888]*nHDs, [0.]*nHDs, [list() for h in range(nHDs) ]\n",
    "print(\"since units are blockgroup based, we assign HD centerpoints to the unit that contains it\")\n",
    "homeU, homeC = [-999]*nHDs, [-999]*nHDs\n",
    "startTime = time.time()\n",
    "for h in popHDlist:\n",
    "    if h%1000 == 0:\n",
    "        print(\"determining homeU for HD\",h,\"time is now\",int(time.time()-startTime))\n",
    "    for c in range(nCounties):\n",
    "        if countyGeom[c].contains(HDCP[h]):\n",
    "            homeC[h] = c\n",
    "            break\n",
    "    if homeC[h] < 0:  #not found inside a county; assign to closest\n",
    "        cDist = [HDCP[h].distance(countyGeom[c]) for c in range(nCounties)]\n",
    "        homeC[h] = cDist.index(np.min(cDist))\n",
    "    for u in countyUnitList[c]:\n",
    "        if unitGeom[u].contains(HDCP[h]):\n",
    "            homeU[h] = u\n",
    "            break        \n",
    "    if homeU[h] < 0:  #HDCP not found inside a unit; assign to closest among ALL units\n",
    "        uDist = [HDCP[h].distance(unitGeom[u]) for u in range(nUnits)]\n",
    "        homeU[h] = uDist.index(np.min(uDist))\n",
    "                \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "dc4a82ce-f310-42d3-b24c-3fa409c740f6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0\n",
      "500\n",
      "1000\n",
      "1500\n",
      "2000\n",
      "2500\n",
      "3000\n"
     ]
    }
   ],
   "source": [
    "sumUnitFrac = [0.]*nUnits\n",
    "for u in range(nUnits):\n",
    "    if u%500 == 0:\n",
    "        print(u)\n",
    "    sumUnitFrac[u] = np.sum([HDwt[h]*unitFrac[h][u] for h in range(nHDs)])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "54a95216-853e-432a-854f-09e82df4acc0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(sumUnitFrac)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "0d579757-3d75-4abe-bd2f-a6caef2b1caf",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "... we add units that were partially included, biasing toward close, mostly full ones\n",
      "working on snapping HD 0 in unit 1651 to whole units; time is 0\n",
      "  we've found a total of 0 HDs that had low contig-unit pops\n",
      "working on snapping HD 2002 in unit 1646 to whole units; time is 22\n",
      "  we've found a total of 0 HDs that had low contig-unit pops\n",
      "working on snapping HD 4004 in unit 2827 to whole units; time is 52\n",
      "  we've found a total of 0 HDs that had low contig-unit pops\n",
      "working on snapping HD 6006 in unit 97 to whole units; time is 68\n",
      "  we've found a total of 0 HDs that had low contig-unit pops\n",
      "working on snapping HD 8006 in unit 1816 to whole units; time is 88\n",
      "  we've found a total of 0 HDs that had low contig-unit pops\n"
     ]
    }
   ],
   "source": [
    "# FROM HERE DOWN, OPTIONS A AND B MERGE INTO SINGLE CODE **********\n",
    "print(\"... we add units that were partially included, biasing toward close, mostly full ones\")\n",
    "startTime = time.time()\n",
    "lowContigPopHDs,lowContigPops = list(), list()\n",
    "for nh,h in enumerate(popHDlist):\n",
    "    origL = ( np.sum([vtdArea[v] for v in HDvtdList[h] ] ) )**0.5\n",
    "    if nh%2000 == 0:\n",
    "        print(\"working on snapping HD\",h,\"in unit\",homeU[h],\"to whole units; time is\",int(time.time()-startTime) )\n",
    "        print(\"  we've found a total of\",len(lowContigPops),\"HDs that had low contig-unit pops\")\n",
    "    currPop, addedUset = unitPop[homeU[h]], { homeU[h] }\n",
    "    if homeU[h] not in wholeSet:  #i.e. HDCP not in a full-district unit, so we can add more\n",
    "        useFrac = [unitFrac[h][u] for u in range(nUnits) ] #[0.]*nUnits\n",
    "        #for v in HDvtdList[h]:\n",
    "        #    useFrac[homeU[v]] += tractPop[v] / unitPop[homeU[v]]\n",
    "        shouldAddUset, hasFracUset = set(), set()\n",
    "        for u in range(nUnits):\n",
    "            if useFrac[u] > minSnapFrac and u not in wholeSet:  #munis more than 2/3 captured should be snapped if contig path found\n",
    "                shouldAddUset.add(u)\n",
    "            if useFrac[u] > minEligFrac  and u not in wholeSet :  #munis that were at least 10% captured are eligible to be snapped\n",
    "                hasFracUset.add(u)\n",
    "        #print(\"the len of the shouldAddUset and hasFracUset are\",len(shouldAddUset),len(hasFracUset) )\n",
    "        shouldAddUset = shouldAddUset.difference(addedUset)  #at this point, this knocks out just the home muni\n",
    "        nJustAdded = 1\n",
    "        while nJustAdded > 0 and currPop < aDP:  #this block -- add all mostly full HDs that are contig to growing list\n",
    "            nJustAdded = 0\n",
    "            canAddUset = set()\n",
    "            for u in addedUset:  #building all neighbors of in-HD munis\n",
    "                canAddUset = canAddUset.union(set(unitNbrs[u]).difference(wholeSet))\n",
    "            canAddUset = canAddUset.intersection( shouldAddUset.difference(addedUset) ) #whittling to eligible list\n",
    "            for u in canAddUset:\n",
    "                if currPop + 0.5 * unitPop[u] < 1.05 * aDP: #prevent big overadds\n",
    "                    currPop += unitPop[u]\n",
    "                    addedUset.add(u)\n",
    "                    nJustAdded +=1\n",
    "                if currPop > 0.95 * aDP:  #it's OK if we go way over; we'll trim back later\n",
    "                    break\n",
    "        # OK, we've added the 2/3 full munis.  Now add more contiguous partials if needed\n",
    "        eligibleSet = (hasFracUset.difference(addedUset)).difference(wholeSet)\n",
    "        for u in list(eligibleSet):\n",
    "            if currPop + 0.5 * unitPop[u] > 1.01 * aDP:\n",
    "                eligibleSet.remove(u)\n",
    "        contigAddableSet = set()  #the eligible units adjacent to the current (growing) set of units\n",
    "        for u in addedUset:\n",
    "            contigAddableSet = contigAddableSet.union(set(unitNbrs[u]).intersection(eligibleSet))\n",
    "        while currPop < 0.99 * aDP and len(contigAddableSet) > 0:  #add close, mostly used munis\n",
    "            canAddUlist = list(contigAddableSet)\n",
    "            canAddScores = [ unitCP[u].distance(HDCP[h])/origL * (1. - useFrac[u]) for u in canAddUlist]\n",
    "            addIdx = canAddScores.index(np.min(canAddScores))\n",
    "            u = canAddUlist[addIdx]\n",
    "            currPop += unitPop[u]\n",
    "            addedUset.add(u)\n",
    "            contigAddableSet.remove(u)\n",
    "            eligibleSet.remove(u)\n",
    "            contigAddableSet = contigAddableSet.union(set(unitNbrs[u]).intersection(eligibleSet))\n",
    "            for u in list(contigAddableSet):\n",
    "                if currPop + 0.5 * unitPop[u] > 1.01 * aDP: #prevent big overadds\n",
    "                    contigAddableSet.remove(u)\n",
    "        if currPop < 0.2 * aDP:\n",
    "            lowContigPopHDs.append(h)\n",
    "            lowContigPops.append(currPop)\n",
    "            #print(\"HD\",h,\" has only\",r3(currPop/aDP),\"pop/aDP. We will swell by nearest units to shore it up\")\n",
    "            canAddUset = set(unitNbrs[homeU[h]])\n",
    "            for u in addedUset:\n",
    "                canAddUset = canAddUset.intersection(unitNbrs[u])\n",
    "            canAddUset = ( canAddUset.difference(addedUset) ).difference(wholeSet)\n",
    "            while currPop < 0.99 * aDP and len(canAddUset) > 0:  #add close munis, biasing towards highly used\n",
    "                canAddUlist = list(canAddUset)\n",
    "                canAddScores = [ unitCP[u].distance(HDCP[h])/origL * (1. - useFrac[u]) for u in canAddUlist]\n",
    "                addIdx = canAddScores.index(np.min(canAddScores))\n",
    "                u = canAddUlist[addIdx]\n",
    "                currPop += unitPop[u]\n",
    "                addedUset.add(u)\n",
    "                canAddUset.remove(u)\n",
    "                for uu in unitNbrs[u]:\n",
    "                    if useFrac[uu] > 0 and uu not in addedUset.union(wholeSet):\n",
    "                        canAddUset.add(uu)\n",
    "                for u in list(canAddUset):\n",
    "                    if currPop + 0.5 * unitPop[u] > 1.01 * aDP: #prevent big overadds\n",
    "                        canAddUset.remove(u)\n",
    "\n",
    "    HDvPop[h] = currPop\n",
    "    HDunitList[h] = list(addedUset)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "7ccd72b7-92a1-49b9-9c47-f326577e107f",
   "metadata": {},
   "outputs": [],
   "source": [
    "for h in popHDlist:\n",
    "    if homeU[h] < 0:\n",
    "        plotPoly(HDCP[h].buffer(0.1))\n",
    "        plotPoly(countyGeom[homeC[h]])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "136a02e8-2eb1-4b61-a580-0a9960d2791e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Lets visualize where the offpops are\n"
     ]
    }
   ],
   "source": [
    "print(\"Lets visualize where the offpops are\")\n",
    "for h in popHDlist:\n",
    "    if HDvPop[h] < 0.3 * aDP:\n",
    "        plotPoly(vtdGeom[h])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "6ca0e286-f4bc-4153-8e53-42e5b6757339",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "lets plot our unit-snapped HD pops vs. orig pops\n"
     ]
    },
    {
     "data": {
      "image/png": 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avgZbKvpwIuyEEZYkUU3nHVj/axXT+fz10nrrRBtsJid/hNGpSWimVZtW/HyEaT/X59MhyqR6oj99rgVbDp3CsF7Jqo4XQiiywN+D+MKNB53/nxRrwt9vzPJpfhGxBYgW4ctGA7Bw/ACvBE8t+u4rh31WE2xez45uz1UMNX0NtlT04RQ8EXbCCHBx5T3z892CtTjqzrW0Kbkuhj9eWm81GsFqJ/V1GJ0a/xQt2qREe8A/n1mf74bDS5Pa5oPVMBoMPh3YAjmI1zS04JGPd2Dy1ek+TZG/+eDJNiHBWoQvOzggMbY1dFqphkkrXypfak9ZM5kO6dHRZ35jwZSKPlg02VoRdj4jPCMyLYhqFyH4Gz8BSI3TnrZdX6FFNlKykwrjT/8UV5RqDzi0ajbqms57dd0PCisw/t0teHRFMca/uwVXvbxB82y2/GAfSJH23R8r8Pv+qT5zoF24scx5D4e9tAEzP9cufJl/N5S8I1q9q/7IfMySydSX32Wgvnml6CkLtb8IW2GkqLxGtHIq0DoB8AvRQL20rEXF5JxQyU4qTiDSPAdKe3DWZnf7d6UXA5uYI7TUYO9Plhcd9ct1rPVNgtpVtfDvhpJ3RIt3VauxhgWhcgmbZgx3a7/S71KJY77eU7v781noibA00wDsE+/9w9KxpsQakJLQWmUjDTY7qb/xd5pnf1TaZYWDcudWIfVxUqwJN+ekIT/TghGZFkFnX39y1uadFikQuGpaWd+RpNhIzB7j/Vjk78zHLOZO1u9SjTlDz6ndA5WFOtCErTDCOvHmZ1rwtzGZAXlptdJoBJOdNFBo4QvC6mzmr0q7rJw+18KUQwMQd4SuaWjBks0VWLK5wjkReCYkO91gw9zVe90F+zgzms47UHdOuM6MP/ldZgr6pLRHhNGIlT8fldSc+gLPyq8s78jphmZM+Xg73jZ6t6LXq/ZU7rv0xjFfr6nd9fosfE3YCiNKJuhAvbRaaTSCrWR3MKJ0dSYWvhwolm2uwNThvSXfAdYID6mJYGRWqmBNGBbBjG9ZjDkCDR4mJy34rrQK35VWITU+Cs/8PhOJsZE4caYJB6rOMkV3eMP9w9Lb3Cv+HXn2qz2w1tsEj9PKAT0YtafB6pgvRzA+Cy0IW5+RYHBkknMGVOJEq3c7aTCj1tlsVFYqZo/pK3nuxBgTYiKFHa2B1ncgIdqkuM2e1Da2yDows0Z4SNm1hRKqib2bnp8e/66+8of+sm3wBmtdE6Z8vB11jc24MSdNdTi0kpEjP9MiuH1UVipeuy1H8lgtHNC1HGv8Rag65gfjs9CCsNWMAP5LrqUWrTUaeraTBiverM7sDg5/+7JE8vy283aca3aI/s4BmDQs3S1Rmlrk1L5K1MJK7dpC7+ag7omCdXXsDg4xkbtwrll77QjfdtfnxqJFTYgxwdzO6KbBsMRHYfaYvpi7eq9XJtLqs8JaEU+8rfgcbNrTUDVnBOOz0IKwFkYA/U/QWgtMerWTBiveOJttKTslG4khJYgArZqTP13bCyt+Puq1Q6yc2leNWljJRCD0bgq9q0XlNT4TRHg8n5vc5DDvln6i44jRaPBqYvGX2l7vizNPtLgvek0qFmzPQgvCXhgB9D9B611gCme8WZ0VHvI+dfjpcy3O2jkPf7Rd1TkMAFLizHBwHFYVHxN9v3gNgRIfF1/Ytb1d6d46MA0x5nb4oPCw7L7/vWBiE4sQ8qxoLIS3E4s/HdCDaazx9r7oPalYMD0LLVAsjPzwww945ZVXsG3bNlRWVuKLL77ATTfdJHnM999/j+nTp2PPnj3o2rUrnn76adx7770qmxye6F1gCjf4FdWBqjNM+wtPytoMKifONOH3/bsgIcakOOcFv1pvOu/Ane9tdW4XGpQjjAaMy07FOz+UM51XboJUuyr1VsC5uk8ndO4QxSSMfFB4GB8UHhaNEOLbLDexeTOx+FttHyxjjTf3JVjKYwTLs9ACxQ6sDQ0NyM7OxqJFi5j2Ly8vx5gxY3DdddehuLgYjz32GB544AF8++23ihtLuKP3CryhCl9Jdfy7W7BwY5nkvlLOZloNMp07RKGovIZJEEmKdXd2jY9p/bfnsULOt3YHh692sidIk5ogXe+h0oyw3mZ55QUBJefg78faUmsbB1xWB2a5ashSjMpKxaIJA5EYG+m2Pdwd0NU45odrUjG9o1gzcsMNN+CGG25g3n/x4sXIyMjAa6+9BgDo27cvNm3ahPnz52PkyJFKL09cQO8qxlBFSSVVudXZkB4dZbUZBgPAiVzMVfvwza7jDC0CZv/+cljionDiTBOSY814/NOdANpeX8j5ljWaJinWhBdv7if6Hnq7KlWbp8UzXF/JOcSckf0VXlpQUom5q0tR09Ds3JYUa8LsMX3D/ntXqnUK16Riesfnob2FhYXIz8932zZy5EgUFhaKHmOz2VBfX+/2R1wkHOsW6AGllVTlVq0RRgNeuqWf5DkevDoDBsiHn7OaLixxUc7VudFokC2J4BoayeqrIbWi1GpVKrYiTryg6WEJ1xc7hxhCoaL+CC8tKKnEwwLf++mGFkz5eAd971CmdQrVKJxgx+cOrFarFSkpKW7bUlJSUF9fj8bGRkRHR7c5Zt68eXjuued83bSgJFQT/QQDrJqBqdf1wrBeyUw+AaOyUrH4roF49qtSN8GA13KNyLQgJrIdlm2uQG3jRQ2Gp/OjGmc+pYMyq8BT13heVMOh5apUbEW8ttQq6yzK+6vYzjvw6q3ZgAH4do+VyY/E9b6tLbXK7u95jBLsDg4zP98t+Bt97+oI16RiekeX0TSzZs3C9OnTnf+ur69H165dA9gi/UAqxsDBOqH0Tmmv6N57TqrJ7c0AB2z4tQp/+2I3ahouCiEJ0SZMGpaBqcN7uU0+apz5WAfbiuoGAMpr6ghNklqvSoUc/OTU9mImzjuuZBtj+PtWUFKJpZsrFB2jlIUbDkqa8eh7Vw6Vx9AnPjfTWCwWVFVVuW2rqqpCXFycoFYEAMxmM+Li4tz+iFZIxRg4fLmi4idVczsjnvh0J+5cshVLNle4CSIAUNfYggXr9guuyJU687E6cc5fdwAFJZVuWYvlEDNP+GtVKqa2lzJxzl93AAkxJqbMl7yGkgW12TLtDg7LNstHLgH0vSshGLJvhyM+14zk5eVhzZo1btvWrl2LvLw8X186JCEVY+Dw9YqKxTlWTjWvxJnPVZsihev1eIFn5n92u5mNxPCcJAO5KmUxcbq2Q0q7VFh2ijnfipKJzTXcufqMjekeA/S9KyUck4rpHcXCyNmzZ3Hw4MWiUeXl5SguLkZSUhK6deuGWbNm4dixY/jggw8AAA8//DAWLlyIJ598Evfddx82bNiATz75BKtXr9auF2EEqRgDyx1XdhVMve7tikqJc6ycal5JboJRWal4LL8P5q/bz3y9UVmp6GA24c4lW0WP4fGcJAOZ6prFxFl7rgXT8vtgxc9HJCcpVk2EUAE8MYTMRyzEmCLg4DjYHRyt5hUQbknF9I5iYeSXX37Bdddd5/w379sxceJEvP/++6isrMSRI0ecv2dkZGD16tWYNm0a3njjDVxyySV47733KKxXJeFatyDQyE0U3q6oWJ1jXXGdEL1Ja52eHKP4ekN6dlQtFPtqVSp3D1gFiPTkGNHkZjysmgixAnieKAkZ9+Rcix13vrcVSbGRuCmni7OeDo0B8oRTUjG9o1gYufbaa8GJJT4A8P777wses2PHDqWXIkQgFaN/kZsopuX3aeNQqhQ1Nn9XR0pvcs6oMf15KxRrvSpluQdK+ik3SWmpoVQaMi5GTUMzlm6uwNLNFZRziAg6fO7ASviGUVmp2DRjOJZPHoI37sjB8slDsGnGcBp8NEZuojAAWPHzEZFf2VFi83d1pPQm5wyfwdda39QmM6vY9VxRk/3SFW8ykrrCeg+0KM3O37Nvdh3HHVd2cx7neR6AXUOpRismRyXlHCKCDF2G9hJskIrR9/grlFpp2CwfDaA25wyrf4LcxBpou7vSvDveaHOE7lmCQDp9pRpKX0bCUA4SIlggYYQgJPBXKDVrenJX9btcRIeYoKTEP4FlYnUViv1dkl2JsJibkYT46EhMGpaOL4uPu6VWl+un2D2rO9cCDsCtAy9BjDkC3ZNicHdeOiLbCSudhe4Pq1Zs9pi+OFxzjikxG0A5SIjggoQRgpBAaWIwbxDzBeoYG4kbc7rg+r4pAAdUN9ic5hUWPB1dlfgnKKl94o3vilohhlUIXFdqxfRPit3a1iEqAoO6JeLq3p1kBQi5FPafbf/Nue29TeWCfS4oqcSzX+2Btd7m3GaJM+OZ32cy+Z/cOywDReU1zMIID+UgIYIBEkYIQoLcjCRY4qJkJ/7lRUcwdXhvr7UAUinOn/h0p9tkKuXn4YqrQKXEP8EAYO7qvRiZlSrbL2+K3wmaP6JNmDQsXfaesgqLSwQypZ5psuP7/dX4fn+1qABhd3B4f3O5Ip8OoT7z9WXa7FtvwyMf78BD12Tgnz+Uy5qPlJrzAMpBQgQH5MCqAt6JbVXxMRSWnaJS0xqit3sbYTRgfG432f2s9TaviqF5XtPVsXNtqVXQQdMzO6snQg6ZSlbJrEXevCl+J+Z8WtvYgvnrDmDQ39dKOmGyOKWyyIe8APHGugPOd2/NruO46uUNmLt6r/wJXPDss93BYfonOyWPWfnLb1g0Qd4ZWCp7qBinXcxRBKFXSDOiEG/DKAlx9Hpv1eTh0Apvwj45oE29leT2ZsXnkeuXWidflr7VnmuR1KxEGA2YPaYvHvm4beoAXssgkYnArY0AJJO/KcG1z1sPncK5Zrvk/rXnWhAfbZLNbwKIm/PEmLu6FCOzyImV0DekGVGAN2GUhDR6vresau7kWOUTvRzehn3OX3cAg+auxRvr9rdqJlRINXL9ZxXCrHWNblqvLYwp1TlIa1bENBeW+CjcNyydqW2+wlrXiPc2HWLat/BQNXO4Mx/aP3tMX9nzsmi3CCLQkGaEEaUhhAQ7er+3rHb6xz/diWfHeafF8XTktNY1qj4XD2/yWPZTBf4wIE3RsUmxJgzqnii5D6vz7tzVe90iWBKi2XxeAHVRQbPHZCIxNpK5sq4vqGloxlmbtFbkIsre7QijAckd2ARgcmIl9A5pRhhRooomlKH3e8tqp6+q906LU1BSiate3oDx727BoyuKMf7dLYr9FaSoPdci6MgpRU1DC/7fKxtF+2R3cFhexJb0rcbDd4G1CByPkqigVufbUgzqnshUmdgXpMZHIUmBWUxN+K0/o70IwpeQMMKIv/JNhCPBcG95O31KnPjkIuesKYWYmcoXzodKlUtSprKi8hq3UFVfoiQqiBdgtx0+7RQk/c3sMX1hiWMTFtqbIzCkx8VcLaxO3HIOvDzz1x0gMzKha0gYYURN/Q6CjWC5t6OyUvHabTmS+0hpccQmGZZoFC1RGqAkJWRpYUZiwWiAm7lIiQDLC5Kp8f59fxJjzU5hQY5//KE/IowGQe3YVS9vEBUkXLV2UvCmzkBHpxGEGOQzwoiWhbEId4Lp3lafZdMC8M6avO/H6QYb5q7eKxgpFB8dyeTI2SEqAmeaWP0PtEUoIkbKeVRrHByw7fBp57WVCrCu+VvWllrbZGBlRSo7ricnzjS5ZdYVO+6hazIwun8X1blaRmWlYkz/VHyzS1zzQdlYCb1Dwggj3ta1IMQJpnvLOgl6OmsKwU8yrBEfroJIlMkIAzg0tvh3pbv54ElnEja1Je/V4pp4To0Ay0eq5PXsiKfGZDodhQtKKvHfkiqmNljio3DHlV0xf90B2X1dBSGxzLpzb8zC6P6pip24XR2dK6rPSQoirpAZmdArJIwoQGxQUVoYi2hLsNxb1sgallU3P8l8UXxMcTuaWhyKj9GChRvL8Nm239B03qGZIMKq8Xn6i904cqrBmZXVGwHWtZ5O5w5RTMLI7DF9ce+wDADAip+PKhKE5AoKKnHirmtsZs4x4kmgTZ0EIYaB41hSAgWW+vp6xMfHo66uDnFxcYFujt+LgYUTwXBveXU6oJ1PR1JsJE43NGtyPiWmhGAkIcaEl27ph1FZqZokyrM7OFz18gbRyZ0XLjbNGO58F8XeAf5NlUp/L8Sq4mN4dEWx7H73DUvHss0Vqp5vqkcfCMIfsM7fJIwQhAqEJsGkWJNsinYx+EkG0EaQuHVgGtbtPaE4fBYIDmHGgIsTvhYCrBrhQsuMwYVlpzD+3S2y+yXFRqrydQGAxQoFJILQAhJGCMLHtElQVt+EaSuLVZ1r+eQhXqnfPXnjjhz8vn8XZ/uS25vx+CfFqKq3SZoWZo/JxNzV2rRBiMeu743uHWOYfGrk0Hqlr0a40EqTx2tnpEw/iV4Iu9Pye+PR/D6qjiXECQZNbqBhnb/JZ4QgVOLqdwC0rm6V4upfEGE0uPkVVJ+xqY5WSY41t2nfs+Mul/WxGJWVipFZFsxfux8LNx5UdW0pVv5yFK/+MdtrQQTQPjpEzq9DCM97rBYWH5ibc9IUJ60DWgWqqcN7e91Gwh291tIKVijPCBEQ9FadVwtyM5IUpTgXcrR0rU1y77AMJMWyn0/w5C7wTsJylWEBIDFG5XVlqKxrUiW0iaF1dAhrbRhfIPd88jMtis5nuPCnl0i0UELPtbSCFdKMEH4nVFcUEUYDJg3LYK78KhcpFGE04O83ZglWpJVjw94qDOuV3Ga73Opf6Nloj3aCp56iQ7RQ2Us9H7uDY4rk4tFbJFqooPdaWsEKCSOEX1Gb2ClYmDq8F5b9VI7ac+K2/YQYExaNH4ghDCvvkVmpGNu/El/vsipqx5LNFYiLjsTU4b3aXMPTtMBrqdaWWv1SVC6vRzL+s/0Y86QqhiXOzJwIz9e2fS0FbDHTj5wph0Orb0h6ciz5L/gQJWHYlGCOHRJGCL+h5YpCr45jEUYDXrqlHx6+EJnhCt+6l27ph2G922otPPFWSzF/3X4sLzqMZ8ddLjohaq0JMVyYFaWcZIf07Cg6qXqeS8q9vum8A2tLrbKTva81cf4UsIMlH08oEwy1tIIRiqYh/AZr+OLyyUMkVxR6MPPICUPetlFsglODAcCiCQORGBvp1l41WVSjTEbJhGsxkRFobG5NYCZ03rcmDMTo/q39lxOEeEElsp0RzefbXpMlp4fUfXQND1aLmhwlWqBXYTwc0GocCxcomobQHVqsKPRg5mERNDxt/8mxZjg4DlvLa1ByrA55PZJFzTRSGiQ1cACmLt/uViDPEmdWlUVVLvPruWY7puX3wYqfjwhO0HNXl8JobL0/o7JSMfyyFAyZt04wZJXXlp23C19TTpsmdx85ALM+3+2VbT9QKnutongI5QRTLa1ggqJpCL/hbXVeluq2vq5MqsSLnp8wzO2MmLJ8O+5eWoSFGw9i4cYy3LlkKwb9fa2g173cBKcGz1tirbdJ+rV4Q7ekaNx2xSWCv3nep22HT0vmzuAgXWVYqkoyy308fa4FCzfI15kRg1T24YdrpWRPEVZvtbSCCRJGPAjFkFO9wK8oxD5RA1o1DGIrCiWrUF+gRhgqKKnEwx9tF5z4a8+14GGBMEA9TlwGtBZ2Y2Hu6r14Y71wjhLP+6RVX4XOw3ruZZsrVH/n3grYRHCiJEyeYIPMNC7owRchlPG2uFmgV6FKVfJ2B4dnvyqVPe+zX+1BB7MJJ87aUHPWxpwQTM5/Qyv4pzH3xizMXV3qdZFA1/uk1SQtdB7Wc9c2tjCZUYT8NEhlH76oSZJHiEPCyAX04IsQDngTDRDoVahSYaiovMat7L0Y1nob7lyyVXF7mlocaG9uBwfH4VyzfNVbtbg+G6MRslEwrFjrGtG5QxQSok2iNXQMaI2qEVNcSE32fBI6lvo8cs9WaqHijYDtLeTIGljId0c7SBgBJbHxN2pXFIFehSoVhvxhbmmwnQcHYGx/i+JcJHLcPywd+ZkW5/0sLDsF23kHHsvvjeVFR2Ctt3l1frn6NPzbMPnqDPzzh3IAbQUgDsDsMcKTvZIkdFLPlmWholW4rRLhgjS5wQsJkW0hYQSUxCYQqFlReGvm8RalwpA//AR4YfmXw7V4a8IAzF291+1dNspoFeJjTIhqF+GmwfGc0IQmPUtcFB67vjfe/6lCVWVgQN6c4zqZD+iWKBoG7Bqh44lcEjo5AZZ1ofLqrdl4ctRlqDlrQ1JsJCzx0YonGCXCBWlygxcSIoVR5cC6aNEipKenIyoqCoMHD0ZRUZHovi0tLXj++efRs2dPREVFITs7GwUFBaob7AsC7YtAsBNIxzGlXvS5GUmwxPlHIKmsa0JirBmbZgzH8slD8MYdOVg+eQgWjh/grFEi1N6XbumHzTPdj9k0Y7ibICIUPVRV34QF6w+oFkSkSIg24d8PDHZrx6isVMwe01dwf6l6IHwSOiFYBFjWhcqdS7Zi2spizF29F//4dh/qGpsVCyKsUVp6iCoj1EE1bcRRLIysXLkS06dPx5w5c7B9+3ZkZ2dj5MiROHHihOD+Tz/9NN555x28+eabKC0txcMPP4ybb74ZO3Yor7fhKwLti0AoY1RWaptJ13Xi8vW1WYWhCKMBz47L9HmbeE6caWpT6G10/y6y7RUrDscy6SklMUZeGVvb2ILCslMoKq9xTqh2BydawVhuAh6VlYrFdw1EqgoBVs0CpLKuCQ9/tB1vrNvPJBDI3WcOwMzPd2PzgWqnej+QUWWEOkiIlEZxBtbBgwfjyiuvxMKFCwEADocDXbt2xZ///GfMnDmzzf5dunTBU089hSlTpji3/eEPf0B0dDQ++ugjpmv6OgMrn0VRTv2udRZFInhRatuf+flun+X14JHK+KjGRs2aaZKVWwemYVjvTpi2spj5GF59HR8d6XXWy0DcA0tcFJ4dJ61+V3KNhGgT8nom4b8lVbL7vnFHDm7MSWNuK+FbwjVzq08ysDY3N2Pbtm2YNWuWc5vRaER+fj4KCwsFj7HZbIiKcl+RREdHY9OmTaLXsdlssNkuOsfV19craaZiAu2LQAQfSnxeeIfdLYdOobDsFAAOgzM64q+f7URVvU1Wy2CJMwMwoKpePKQ2KdYEa30TCstOCU6yanx0tDRLJsSY8PKt2YpX67z6+r5h6Uz7S7VZzT2Q8xOSw1ov78Oh5D7XNrYwCSIAaXL1BrkDSKPITFNdXQ273Y6UlBS37SkpKbBahT35R44ciddffx0HDhyAw+HA2rVr8fnnn6OyUtw2Nm/ePMTHxzv/unbtqqSZqqAkNoQviTAaMKxXMqaN6INhvTqh5lwzxud2k53gDACeHXe509wjJg7XNLRg2spijH93C656eYMmtmctJ7OXbumHCKNBNvGdJ/z9+aL4GNP+ye3NmiYtlPITUoKn+t01uWL1Ge+ikjyRSx5IBAZyB5BGkZnm+PHjSEtLw08//YS8vDzn9ieffBL/+9//sHVr21wJJ0+exOTJk/H111/DYDCgZ8+eyM/Px9KlS9HY2Ch4HSHNSNeuXf1SKI9CrghfIeRFnxBjAgBBEw5LVIsQLAXkhPB89wd1T8T/e2WjrPly9pi+baJ4xPrA9+NPF6oaKxEVkmIjcbqhWbQtCTEmmNsZ3UKOk2JN+PuNWRjdv4uCK7VFi+rGvPpd6FxSUU9KUPvsfYlextRAtyNc3QFYzTSKhJHm5mbExMTgs88+w0033eTcPnHiRNTW1mLVqlWixzY1NeHUqVPo0qULZs6ciW+++QZ79uzRtDMEoVfW7DqORz5u67TNDzmP5fdBt44xsqGh/IBqrWuUzNOhdGATCzccl50qmOPDc9JzbVdNQzOS2pthiRMf8NVM7vcNS8eyzRWCbZEbxB66JgOzRnvnTOw6mSW3N+PxT4qZzGw8b9yRA3M7o2bVmIXQW4ioXsJY9dQOIUFcj0KkVvhEGAFaHVhzc3Px5ptvAmh1YO3WrRumTp0q6MDqSUtLC/r27YvbbrsNL774ItM1SRghghW7g8Ob6w/gjfUHRCcgFsHBc1XncHBMWVtZnOHEclbw/L5/Kn6pOO2WiyQhxoRJQzMwdXgv1as4u4PD+5vLRaNkPFk+eQjqGpsFJ5XGFrusg/BbEwZidH/tBnq5++bJv+8fjCc+2ykpgKnRkEy9rhd6p7TXnSZX7P74e+LVSztc26MHwchf+MSBFQCmT5+OiRMn4oorrkBubi4WLFiAhoYGTJo0CQBwzz33IC0tDfPmzQMAbN26FceOHUNOTg6OHTuGZ599Fg6HA08++aTKrumfQKsDCW3w9jmyRtEI1bRxve7phmbMXe1h3ok2MbXheG0jNh+sxk8Hq3HsdCMADmlJMRjaIxlDLlzrb1+USE6o3+yqREqHSIztb8GPB06htrEFtedaMH/dfqz4+YjqQTTCaEByBzPTvgnRJuf998zeyyqYzV5VgpFZ2mVR5v3Mnv1qj2Q2Wl7YhAGymiAHBzw1ui8WbjiAuqbzTO0Y1itZd9EXeslqrZd2uEI1bYRRLIzcfvvtOHnyJJ555hlYrVbk5OSgoKDA6dR65MgRGI0X/WKbmprw9NNP49ChQ2jfvj1Gjx6NDz/8EAkJCZp1Qi12B4ctZadQeKgaQKun/ZAeHb16KUJR6g1m4Upt2719jkpXzUCrFz2r+YI12dgTn+4UbMOijWWIiYyAwQA02OTr2lSdaRZMN8/n1JiW3xtTh/eWvbeezyM5lk0Yye/bGd/sOu58hq6T7ypG59ZTDc14/JNiXJIYjbwLwpjS99ju4NyiovJ6JOOHJ4fj7e/LJNPOzxmbieqzbI6qlXWNMDC0ixdyBnVPRGHZqYB+n200dxyni6zWes2uTTVt2qLYTBMIfGGmEVu1JsSY8NIt/QQnHLmJTW/qQC0IZuFKbdvVPEc3f4JYMx7/dCdTkTxXpuX3xoJ14uYcvSOXU0PoecRGRoDjOJyTqD7s6RPieh27g8PSTYfwwppfFbfX81t3+r3UN7Xx3QGAhRsO4p0fytoUJYyJjMBD1/TEWVsLlmwqdzOzGA2ttXWeHNVXkUmKBQOAB6/JwFc7K93uaVKsCTfnpDnrCvlaMBF0zGYsUOhNLhSWhcaq4mN4dEWxT9tBSOMzn5FAoLUwUlBSiYcvOBGJsdhjwpGb2HhPaTEpPBg9pZVOynrSoKgVDJvPOzBk3jrUNEjXMnF9jlpEWsREGhEXZfK6+JweeGvCgDbRK2o0RXKM7W/BzxWnvb5ni+8aCACizzAhxoTm8w5VlZF5QSohxsSU9E5JNeT8vp2wfu9Jyf29XTioXYCxojbBF+tCI1wTjekJEkZEsDs4DHtpvewAluoy4bBMbFpkiNQTSoUrPWlQ1AqGBSWV+NsXJbIF3IBWZ0Sj0YB1pVYsuRDhQbRiNAB/Gd4bGZ1i3UKEvRHWfElspBHnmh1Bq5GSwhutrLcLMLl2qV2cKVlosLZRa+dm4iI+c2ANdlrVsPIrKd6OmJuRJOsA9dQXJbihn4Xp+q7Z9fSkSfBEia21rrFZVxVE1diJla7wJn/4i6qVcjjg4IAF6w84/x0bGYEGHd+rhmZxE1Gwo9ZJk6UqcHx0pGpBBFCX1VqpQ2qE0YDZY/oKhtW7Mnd1qabOzYRywk4YUZJq98SZJqaJ7VRDMz7acoTpnHx2PaWaBH8LLqz3yVrfhH8U/Korb3WlaZelBjgxSBBhR8+CSDig1EmTdcJ/cuSlTNf39B+xeKExVbPQSGRwkg6EEyvhTtgJI0pS7XbuEKVZnQBeLZmbkcS06lDir+ILWO9TzVmb7rzVlaZdlhvgCCIUYB3LWCd8FnMmACyaMBBGo0GThZSa+i5UEyY4UFSbJhTIzUi6UHhMGr62gxZ1AlzVkgAUlZHmBRfPwYEXXLSoQSKEXA0Rvv5FUmwk0/m0+NBd63lI1R1hbTsfJUGDEBEOsNbtYf0ektqbmb6zIT07Iq9nR9yYk4Y8FeHUrqip70I1YYKDsNOMRBgNeHbc5bLRNLw909uqnYC7WrKw7BSzJoHFX8VXJhDWSsbx0WzCCD8QepNATE475GrKuuPKbliwbj9TFWYahIhQhq/b8/gnxW7+cmLaVdbvwRIX5fdq53LjsasG2ptjCP8TdsII0JoBb/FdAwXzjCTGmDDPJfdAhNGAcdmpeOdCfQ4l3JPXHTdkpbpNvGtLhasbe8Lqr+JLEwifYdJTCHAVrprPO5AYY8JpkbBFpQOhECxmLaBtaKZQETohe7UWAidBCKEH510OEPw+hczCdgcHh4OTzBPiOnlHGA2yY4Q3CPnKqRGA7riym2BSOrVCk7c+fEqP13Owg1aEpTACXEzJK5eBtaCk0lkoTCk3ZKW6CQl2B4cvi48zHavEX0UrE4jQyy6Vulgu3Tk/WLAOhGLtktMOzfp8t+A1hNolFMne6nGfiUc+ltaWEYQSft8vFd/s9o0ZlZWkWBMcnMi3AHft6tpSq2y+HKHJW2qM8GYSldKGsgpAcjmA1AhNWmRnFjp+9phMJMZGCo6zekmb4EvCLs+IEtTG0YvF0LMm4EmKNeHnp0Zg4YaDkimmebzNXaLmZWdJHCekmXCFJdcA6z1jRSgXgZRQFWUyokkiOyhB6BlWzcy0/D5YsG6/rGZQi0mX5XiWXCJy9V3kwvVZSxgobZea7M5CuFbNDuas3qzzd9g5sIrR2GzH7C934+4lWzH7y91obLarirKQUvuxajBuzknD2lIrFsgIIryDGF+bQs4xTQg1DrJ2B4dnv9oje26jwSCZddLVzCSG1s6lnk7CvFAl1k4SRIhghtVEtGxz2wnPlYRoE/79wGBsmjFckWlVjeO9nDYUaP1+AYg6xsqF6xsArPj5qGw/1LRLbPxVmkKgsq4J7wgIIqzXCzbC1kzjyuQPfsba0hPOf/94APhwyxFkpSnXwkip/Vgdw4b3TREtcOYKB2Bcdmqb7Jasqw+7g8PMz3crdpBlTRzHGvonJXD4wrmUF4K2lJ1iEqoIItSRqyNT29gCcGDSIqgdV3i08JVjPcf7m8uR3MHMZELytl1apxAIVJE/XxH2mhFPQcSVkmP1is41e0xfyZUDa8gpOPlS4wDw+/6tKjy1q48Zn+1UpbnQWlshJXDI3TNvKDxUHRK1YAjCH0z5mC2VwMINB7zSiFrrGpnaIzUOsY5Rc1fvxaMrijH+3S246uUNkv3z1ofPVykEQiU1QVgLI43NdlFBRA3JHcyyHtHDenYUDS8DLpQab2CbIDcdqBZdfXAAZv5nNzYfrG6jxisoqcSwlzbgs+1spdc9U9hXn2GfwJNiTcz5PoTgQ4z5/T2PF9rOTmh5oxOEL6ltbJFd5DSfd+CfPxxiOt+JM01tcget2VXJXNlYahGjRqMqt4hjPWeySMZXX6UQ4M/LmodJr4S1mebFNaWank/qZZu3phTv/uheXtwVz1wkLLCoVu98b6ub2UZNlU2pFPZStHqI98WUj3d4lYdALMQ41twOZ23nFYfj8o6z7RQ4rpnbGWE7T/4jBCFmYuELTbL6qVRUn/MqQEBqETOoeyKMBoiOt0LImZBYUwA8/ulOPDuurZmcP14rU41nVu9gj7gJa83IL4dPa3IeuRX+vDWleOcHcUFkbH+Lm3mHxZyTEG1ibh8v8a/ZVam4BktCjMkthb2SD2nO2EyM7t8Fb981EJZ4d0HNEh+lyBN8VFYqZo/pi6TYi/0+azvP3BZXeF+bN1yKuUmRGh+F+bdlq7oWQYQSYiYWfnxg9ROLbGfEgnX7VU/McouYbYdPKxJEeKRMSFJaWleq6oU1LK7HK0VMKzxnbCbWlloDkqVba8JWGLE7OBw+dc7r83imevdUkzWfd+DdH6XzlKzebXVTqbGYJiYNS2duI3/m2atKFH/8k4ZmABBPYS9EYowJi10EjVFZqdg0YziWTx6CN+7IwfLJQ5i98nkKSiox5eMdqGmQ1gax8OfhPfHVzkrm/ozLTsXo/l2w+K6BznBlgghnPE23Shc5LecdqhIMJsWamBYx3vpRiB3Pa2lTJEqKSEW6jMpKxbT8PoraEmuOaHO9+GgTHsvvjeGXpUhG+HAi7dAjYWumKSqv0aTyKm9eAdBG5ZgaH4VhPTvKSugODviwsAL3X93DuU0u++mITAtW/HyUOWsoX11YCQkxJkwd3ovZC/ymnC744xVd2ySOA1oFLLUe32oGOymWba7AWRv7s//kl6PokxKHwrJqScc8gggXXE3SaqJE1H7Ls39/OdMixlv/DKnjR2WlokOUCXe+t1V0H6FIFz4BXLeOMUiMaYfT59g0uw02O/559xX4peI0lm0uR21jC2obWzB/3QG8/1OFaPZrnmCJuAlbYUQLD+TZY/ri3mEZTjWZULpyVifRwzVttTRSmQ0BiKZF1oqXbumHiAvVNlm47rLOGNYrWfN2aB0Sp0QQAYDT587j8U93anZ9gtAzUuOJkL+GP6M5LHFsQoY3/hkJ0SbZOjXVZ9mc+Pl7o9TfzpMlP5Zh4762AQtyggjP8Vq2CKVAErZmGm8lZwOAu/PSAchX4WWhe1KM4HZeoyCU2IfXnnj6Y2jBtPw+zhWI1lUvlXp9h0roGkEEA1JfI4e2/hrJ7eWroHsLS+SdK3yJBzVMGpYu61SvZEzkEyt6s6DaICCIKOHZr/fo3nckbDUj3hZH4wC8/X0ZcjOSvF61Gw0XBRuluNbYmfLxdtkIG1Z+tdbB7uCclYsTYkySJorEGPnVBKAuRTRV1SUIfZAYY8KITIv7Rh+7I7BG3nnWwYlX4d/V3twOf7q2l+y5B3VPZBoTB3VPRO6L6ySv6SvNtitnms4z1QILJGErjPBOot6YOeav24/7FTiSijH56gxEtlOupPL8QF68uR+mXCj25u3L/d+SKgz6+1q8dEu/toOPACzXY6m+K/ShUFVdgtAHp8+1tPE/YM2LpBahrNaeY9/pBhvmrt7rXrVbQcQhz1nbeQyZtx435XTBiEwLcjOSBAsIWuKi0CwT6s8BeGvjQVk/M3+Oaa5hy3qrBBz2hfK8teUlxZqYIjxMRgNaPMwRBgPw4NUZmDVauTpRTMMwLjsVX+2s1DSW/bH8Pl4X7JMrOihXNI8XZADhjzfGZMQ5FXVkWJ8fQRCt3D8sHbPHXu78t5bFLBOiTXjx5iwkxpolC+B5M2Yrao+M9kOOqHZGNOksP9HyyUNQ19jst7wkVCiPEdew0/suaDmUyIY1DS1Iio2UPcZTEAEAjgPO2zlNi9v984dyPHVDX8we0xe/y+zMfE4xOADLfpIOTeaR8u1QUteBx9W3JD46EosmDBD1j1EjiKTGR2HLrHwsnzwEo7NSFB9PEOHIks0Vbv4HuRlJsEiEuiph0Z0DMbp/F1E/uTW7vPe/UIK30XN6E0QAYJ1O85KErZnGFd5JNK9nR+RmJCmWugdnJKGgxKrq2ks2V2DJ5oo2UimvQrPWNaKmoRlJ7c2wxLXaKuUcZv+ycoeqhD9isH6QUr4d1npldR2EVj+WODMGdU/E6t3q7rUnjS12bPi1CqOyUpGbkYQtL6xjTtpEEOGMq7p/banV60mX14wO6SEefrpm13FMXb7Dq+sQwBfFx1QXMfQlYW+mEaL5vAND5q1TpL5PiDahrqkFau8m/9jfvmsgAIgKRIkxJuZwLi1JiDZJOsemiphYms878LfPd+HrXcdhOy9/c3gVotKU9WpwveejslLx/Nd7sHRzhY+vShChwfLJQ3C6oRmPXPBT8wYD4OYzZndw2FJ2CoWHqgEY0M5owALGjMmEOO0vlNCQQ8rkrhTW+TusNSNiDjzbDp9W7EfgbRQLL5U+8ekuyZclEIIIAHTuYJbs47js1DaCyLw1pfjnj+XMAlpSrAmVtY34+xrtEpxJwV9j+ic7cbTmHNqbw/pzIAhFfLenEv8qPKzJuVwjXwpKKjHz892UYNAHsJbQCEQ6hbDVjEiFmDY22zHtE0pypYSEGBMWjR+I6gYbOneIwoZfq2TT4BMEQbgytr8FX+/SxgxLqCcQmpGwFEbEQkz5EN/YyAjmypMEQRAEIUaE0YBok1Fx5udAIBfVqAaKphFBqs4Jv40EEYIgCEIL7A4uKAQRHrnkcr4i7IQRreucEARBEPrg9/31mV3UVyTGmDSrJM5aEdlXhJ3HHtU5IQiCCE1W79J3/RUtmXpdL0wb0QcA8NOBajz80S9oUJFviYe1IrKvUKUZWbRoEdLT0xEVFYXBgwejqKhIcv8FCxbg0ksvRXR0NLp27Ypp06ahqSkwQgHVOSEIgghNdO8AqSGJMSbYHRwWbjiIyR96J4gA7BWRfYVizcjKlSsxffp0LF68GIMHD8aCBQswcuRI7Nu3D507t834+fHHH2PmzJlYunQphg4div379+Pee++FwWDA66+/rkknlOBNaWmCIAiC0ANzV+/F3NV7NTvflkOnAlqfRrFm5PXXX8fkyZMxadIkZGZmYvHixYiJicHSpUsF9//pp58wbNgwTJgwAenp6fjd736H8ePHy2pTfAVfII8gCIIgiFbeWH8Aw15aH7B08IqEkebmZmzbtg35+fkXT2A0Ij8/H4WFhYLHDB06FNu2bXMKH4cOHcKaNWswevRo0evYbDbU19e7/WnJqKxUPHZ9b03PSRAEQRDBjLXeFrD6NIqEkerqatjtdqSkuBcVS0lJgdUqnKhmwoQJeP7553HVVVfBZDKhZ8+euPbaa/G3v/1N9Drz5s1DfHy8869r165KmsmEQ//pVQiCIAjC7zz3dami4q1a4PPQ3u+//x4vvvgi3nrrLWzfvh2ff/45Vq9ejblz54oeM2vWLNTV1Tn/jh49qmmbCkoq8X8bDmp6ToIgCIIIdoQqqPsDRQ6sycnJiIiIQFVVldv2qqoqWCwWwWNmz56Nu+++Gw888AAAoF+/fmhoaMCDDz6Ip556CkZjW3nIbDbDbNamJLUndgeHxynVO0EQBEGI4u80GIo0I5GRkRg0aBDWr1/v3OZwOLB+/Xrk5eUJHnPu3Lk2AkdERAQAIBCZ6N9cv58yrBIEQRCEBP5Og6E4tHf69OmYOHEirrjiCuTm5mLBggVoaGjApEmTAAD33HMP0tLSMG/ePADA2LFj8frrr2PAgAEYPHgwDh48iNmzZ2Ps2LFOoYSVc83n0a65bdVBo8GAKFOE235C2B0c/vnjIUXXJAiCIIhwo29qhzZzaTujEZHtWpULDgeHpvPiC3vXfVlQLIzcfvvtOHnyJJ555hlYrVbk5OSgoKDA6dR65MgRN03I008/DYPBgKeffhrHjh1Dp06dMHbsWLzwwgtKL43cF9bDaI5ps/26Szth2aRc578HzV2HxhbSfhAEQRCEGnKeX9tm26PX93ZmfT148ix+N/8H0eMfvKYH/ja6L/P1VKWDnzp1KqZOnSr42/fff+9+gXbtMGfOHMyZM0fNpQiCIAiCCHEMXCAcNxTClyCuPHlKsAQxq5lm66EaTHr/Z5+1kyAIgiBChWX3XonBPZKc/1ZjpuHn77q6OsH527m/ds32PTGR7RATKd9ksX2u6dMJSbEm1DS0aN00giAIgggp6ptaROdTo9HANB+z4vM8I3oiwmjAzTlpgW4GQRAEQegef0bUhJUwAgD5mcL5UAiCIAiCaCU1Pgq5GUnyO2pE2AkjfNVegiAIgiDaYgAwZ2ymXyv4hp0wEmE0YFx2aqCbQRAEQTBgVpCrgvCe1PgovH3XQIzK8u88GXZP2e7g8NVO7SoSxkYa8daEAVh818A2GhdPoTIh2oRp+b3x1oQBSOkQ6fZbZIT/JFCCIAi9YwDw2PW9Ufr8KEzL76P4eJMfV/VaER/VDrcOTMPdQ7p5fS613Q9UgG1QRdNoQVF5DSrrvM+5f1NOF1zeJR7J7SORGGtGbkYSRmRaUFRegxNnmtC5QxQGdU/EtsOnnf/OzUhChNGAgpJKGAzucmBSrBmZXTpgw68nma6fGGPCPXnd0S0xBs9+U4ozTcLhzL4gKdaE58dejqkrikX3GZ2Vgh6dOmBwRhKMRgNOnLHhZF0TSo7X4lhtE3Yfq4Ves/InxJhQe44irghCazrGRmJcdiqW/XRYdl8OgMFgQITRgLrGZsXXenPCADgcHJ5eVaL7CMqEGBPevH0AjBEGVJ+14cf91V6fc/LVGfjnD+UAWu8lK1X1Nvzpo+1+144EVZ4RuThlFlYVH8OjEpMoKwnRJtQ2XnzBU+OjMGdspuzDKyipxJ8+2t7m5TBA2QvjbEeAJs7lk4egrrEZz31d6ibcid2HgpLKNvvqlclXp6O92YRlmyvcnjFBEN6jNL3CQ9dk4J0LkyorY/tb8OaEQQBateH8IrGi+hyWFx2Btd4345Alzoym8w7FY/KIzM4oOVav2fh4/7B0zB57ueC4ywuEq3ZWoqZBWMgzALDER2HTjOFe+42EZJ4RLdAqVMlzkrLWNclKk3YHh+e+LhUUOtRKhIFawZ8404Qbc9LaaIN47Y8rYgKYXnlvUwX0L6ITRHCiVEvx7o/KBBEA+PHAKdgdHCKMrZqVvJ4dAbSOwVd0T0ThoWoArdvrzjVj7uq9XgkCCdEmLLpzIADgzve2Kj5+bekJ1dcWgo8aHZWVKjhGF5XXSGqnOACVdU0oKq9x3jtfE3bCSG5Gkk+0CRxapcnnvi7FiEyLoDSplYlID/BCneuHLoSUAKZXSBAhQhWDIfjeb4eK9tY2trSZSIW0BP/Z/hvmjM3EphnDUVReA2tdI+au3ovTDc2Kxqzaxhb8UlGD9ORY5Y3VEF6j4RqSKzRGnzjDNg+x7qcFYefAykJsZATUKKZcpUkh/PlgfYmS+PNQEsAIItgJNkHEG1zHW1476zkW8RrttaVW5PXsiJsHXoIXb84CAMVzwPx1B1BR3eBts71GKiTX7uBQWHYKB6rOMJ2Lkp75kKLyGlmtSEOzHbcMTFMlkADiQoc/H6yvUBp/ricBLMpkRG56YqCbQRAB5frLOrWJtDAaWh0e/ZGDKdYcIb+TBvDjLYt5/LmvS2G/oIIZlZWKt+8aCIuKe7G86AgscVGq5w5vkAvJLSipxFUvb8D4d7dg4cYyyXMZ4P+kZ2FnpmGdHP+z/Zjqa4gJHXzCNWtdky7NFnJOtKxOuq7oSQBLiDbhX/cNxuVzClSpfrUiup0Bjef1+AYQ4cB6gYg9jgPe+7EcD16jLgKDldT4KNx+xSVYsP6gD85+kcQYk3MildPOCvlHuPpaWOubMPebPUy+LtZ6G6bl98GCdfs16YcnvJDzWH4fdEuKRk1DM5Lam2GJE/bX41Hjt+fvpGdhJ4z4cnIUste5EmE0YM7YTPzpo+2qo2d8xbT8Pljx8xG3jzYh2oT8vp0xrFcyLPHRki+7GHoSwKz1NhQfrcXkq5V752sJCSJEoDAahH0weJ+3r3ZWYtGEAV47dArBa1VHZFrwfuFhnzrfnz7XgrWlVozKSlXtH+HqaxFtMuLhj7YznSc9OQZv3zUQz361B9Z6m7KGy2BRsSBU6rdnNAALxw/we9KzsBNGfDU58lO0nDQ5KisViyYMvBD7fjGsSmyQcJ7fw/FMiRNufLQJdSIhqrwANXV4L0wd3ks2MkYprgKYr1ByL06cacKs0Zk4eOKs4AqRIEIZqTGG1xAkxpqdDp3/LanEB4XyOUHk8NSqvnRLP9mVemKMCRzHobZReQ4l12CCiupzTMdILVRHZaViWn4fzGfQeHTuEIW8nh0xItOChRsOMh0jhKsWJD05RvWYrNRvz8EBibFmRdfQgrDzGeEnR0C5g5IUFsYUugUllZi7utRNEEmKNeH+q9JhEGgTv23R+IFYPnkI3rgjB8snD8G2p0cwZyW8b5j4uYGLAhS/ErgxJw15PTtqpqLjBTDW06XGR2Hy1emy+xsNwFsTBmLb0yMwe0xfpnPzA84DV/dkawxBhACp8VG4b1g6074nzjQ5x4IbVKyODWjNt/HvBwY7x6tNM4a7jY28X4anj0rH2EjcNywd0/J74/S5FlWCCHBRsNpSdgrLi47I7m+JM8v6R0wd3guWOPFJ2tPPIsJowKP5vQWzc7uSGh+Fh65p66/DzymP5vf2akxW47cXCF+/sNOMABc/BLVJuHgTy60DL0GMOQLdk2Jwd146ImVqKIjZ7U43tOC9Hyvw4DUZ+GpnpVubpNRyU4f3wvKiw6KqwItaj9641NKhTX/VqPzUkhgbyeSnMXtMX9w7LAMRRgMGdE3CIx+La1QWjh+A0f1b237vsAy8t6lcVOPlaUKT05Dx+796azbW7rXiX4WHwyoSgQgd+G+qqLwGSzdXyO7vqiFQqknmp8pnx12OYb2SJfcVy4EBAFe9vIHhavIUHqpmSnA2Preb7EQfYTTg2XGXO7W8rvdDSjPu2c/k9maAA6obbG7ajidH9dVcMw2oc00IhK9fWAojwMUX5P3N5Zi7eq+iY+NjTACAz7b/5tz23qZyyYnd7uDw7FfiHt28vfZ/f71OMIW8EEo+DrEP318OSqySdnIHs7NNo/unYrGxrdAo5Egr5Y8jNFCw7j+sdzKMRgPeZ0hfTRB6hP+mWAVwzxwVSvzclC5whHJgFJad0tBfhW18Y80PIraQleu3XD4m1n3UoESglPN79CVhK4wArQ+fdUX96q3ZqG6woaL6HBas299mX7kMrAs3HJCU0Hm14rbDpxW9kEo+Dl+97CwkM9ogPSVyJUKU0oGCdX89hScT+iYhxoSodhE+SzeuBtcEhUoEdh6x7yQ1Pgqzx/RFYqxZ0wUO6/cWExmBcyIFrvhxe3BGEhZulD/XPms9CsvY2h/ohZ0crunv+baxCJSsfo++Iuxq0wjBm08A4Q/07bsGYkSmBVsOncKUf28XrVfimc+ffynWlVqxhEE9CgBv3JGDG3PSFPdB6AXUy8dRUFKJZ78qlRyg1dZCEOo3AEX3Qu7eFZadwvh3tzC3iQhv/n3/YBiNBiz+Xxn+tz+wTtKpAt+UUCZSlrB9f40xWn1vi+8aiA5RJkXp2dWkL9ATUs8WgKRrgq/6TrVpFCC3QgZabZhyqkPXeHWhInIsqLXVBVLrIQVLfLtaiVztoOqJ573jsxS6Vl9OjY+iTLIEE4WHqjFtxKUoKq8JqDAilKDQ7uAQHx2JJ0ddhpqzNiTFRjKH7XszxrgKMmI+EzwsZgW56MPEGBNGZFrwza7jitrJUmNMr4iNta594qOkTpxpatVWG4Dqs8LPwd+QZsQFIcl/balVcbKY+4alY9nmCsWhw0KrmGDG7uCYhDhLnBnPjrtc8OMXW41JVT8GoHowERNwft8/VVXBLiI8YQ03b2cAfJF2Rkgo10p4V4pcxW6xtoppq1lv1/LJQwBAsZZFy4q1/kJurA1kn0gzogKhFbKaIm9fFh9XlcMkULY6X8Ea3/7abTmCnvdig+fsMX0xd/VeSWdgqYKFYkitLEgQIZTAmvdGa0EkIdqEiUO744ruSdhaXoOSY3XI65GMusYWTPlYetXsC4GERTMq1AYpbfXoLAuT2fvEmSb8vn8XxXmlAlGx1lvUZJnVGySMSKA0WYwBQGKsyS2HCCvT8vvoQi2opV2Y1RGtsOxUG1WhlGDwyMc7JM+n5sNjqV9BEFoSG2lEQ7ND03PWNrbgDY9U6ws3lrUmTRTY3xvhXQ7WxZxYG8QcRYvKa5iEkc4dorzKeh1MjutKsszq1b+QhBEJ1LyMN+ekMTur8ljizJg6vJfz34F6WbRW47L6vyzceHHwbNV8ZGLuau8FAyXPj6oLE/5Ga0FECiljvK9WzUq+KbE2CPmpKA1RVptXSk91teRgbWtF9bk25hy9OO2GXQZWJSh9GR/L74P8TAvz/nxW1GfHXe4UNlwrKz66ohjj392Cq17egIKSSkVtUYpciW011+cHDSViVKvmo2071KDk+QXTKoggfIHW34CvMn9KZdEWc4YflZWKTTOGY/nkIZh/ew6SYk2i5w9ExVpvkRtrDWj1Y1qwbr+mY7yWkDAiAf+AWUlPjlE0AXumkPeFQMCC0hLbrKhJva+FSUTNYBJMqyAl3DowTbAUQCgSJZMBmZAmub229Uh8mfmT13ZYRFKoC63yeS3LzQPS8OLN/ZhKZAQLcgIaP65qPcZrCX29Erg+YBZ4G+XsMZmi6kOgNdrGs16DrwQCFpQ4P/Fhr6uKj6Gw7JRse8QGDa3QajBhXVkkxLRdUbU3t8O9Q7vj1oGXID5afMUVCK7u08mn919PNJ33n9kjFHn8k2JNFzxKFmZqFhCu2g6xGjhSxyoVZvSOVJ+m5feWdKp2HeMDBfmMyDAqKxVvTRiIqcu3y9ZWOd3Q7CyEJ4RUyuBAekOzqlPXllox/ZNixfZGT0e0A1VnsHBjmer28jZh3reENS2zlC+OXHZKDuIREg228xjSoyNGZaU6r7Hp4Eks8qKPWsFXEHU4OEnH39jICNg5Dk0twT2hJ0SbRJMSEtJU1ds0jaxhrdgtt4CQ+27Vjod6z6SqBrE+seZbCaS5moQRBkb3T8X/OXIwdUWx5H5PfbkbpyWkz9lj+op+5Eq8obWGVTUqVGSLNTTQddAoLDvFLIxIpa0elZWKkVlsgwmLc66Yo1tKnBlN5x2SKwvXSAB+8g+0MGI0AIO6J8Lu4GTrL3WIaoe/jboMj36yM6ijh/paOqAwAKu7WHMEGmzCqcmDBV9E1ozKSsWD12TgnR/EQ+MTYkyYd0s/wfHD17lR9Jos0huE+sQ6xgfSXE1mGkbKqhtk95ESRAwA5q7eK2rWUPKyKDWVyMGiThUbl9SYkFhMIqnxUXj0+l5tzB6ealT+w5Mqsa3EF0dI9fvabTmKVZx6cIh1cMC2w6eZohqs9Tb8JcgFEQABEUQA4N6h6QG5rtZoqa63OzhsPliNlT//JrmfuZ0RIwQc/wPlQxeKsI65gXTaVSWMLFq0COnp6YiKisLgwYNRVFQkuu+1114Lg8HQ5m/MmDGqG+1v7A4OyxSG63oi95GzviynG2yaR9uweKdLyRlKBzAWZ6vGFjveWH/QqXJPiDZhWn4fZpswjxpfHE8Bp/qsjelargKImlwzvuDEmSZdCEahztAeyYojx/SMN++M3cHhjXUHMGjuWtz53lZZs5m13tZm7AikD10ooiYCyd8oFkZWrlyJ6dOnY86cOdi+fTuys7MxcuRInDhxQnD/zz//HJWVlc6/kpISRERE4I9//KPXjfcXReU1mtmhxT5ylpdlXHYqpny8wycrBSnnp/uHpTOdQ8kAJnY93kHUUxNR19iCBev2Y22plfkagDJfHDHUqDiTNI5MUEv1GZvmURKEO5Y4M4b07Kg4ckwJJhWThLmdEaMuT1F1PbXq+oKSSgz6+1rMX7df0ZjpOXZo8d0S7ujdaVexz8jrr7+OyZMnY9KkSQCAxYsXY/Xq1Vi6dClmzpzZZv+kJHe1z4oVKxATExNUwoiWK0upj1wqBbJcIjAtbL1aZDz05nrJ7c14/JNiwX3V9lELXxyWwl2WOLObitMSp4/olbmr9yKlQ2RrBk5aRPqE+qbzWLjhAKYO7y2bXCsxxiTpDC1GiwoNgO28AzcNSEPf1HjMX7ef6RjPhGFKKCipxMMyzqpieI4dgfShC2X07LSrSBhpbm7Gtm3bMGvWLOc2o9GI/Px8FBYWMp1jyZIluOOOOxAbGyu6j81mg812UTVeX1+vpJmao4VTD+tHLiUQ+CPaRouMh2qvV1h2CtZ6cZOImj5q4bjFklK66bwDa0utztUFf8/0kNW16ow+TEahyrlmO+avO4BlP1XgpVv6uVdGFahQC7Su/DcfPOlVVBkASSGTF96fHHWZonOqUdfzZhWliI0dweBwGazo1WlXkZmmuroadrsdKSnuqr+UlBRYrfLq86KiIpSUlOCBBx6Q3G/evHmIj493/nXt2lVJMzUnNyNJMmOfJ97a5IScMgO5UlBib/TGudYXfdTKcYvXWsUL5BkBgLpzLW6mMqU5aojgp/bCO7C21Or8fof1Ssaw3slu3zL/ffdO6aD6WjGREbhrcFemNO81jD5PHWMjVavr1ZRTkBoXg8HhktAWv0bTLFmyBP369UNubq7kfrNmzUJdXZ3z7+jRo35qoTARRgP+fmOW7H6p8VF4a4JvbHKBXimw2Bu9TWXviz5q6bg1ItOCqHYRgr8JOdWNykpl9rcJRpQI6OECBzbHSruDQ/UZNiFBiHPNdny0lW1cTIqNlHWuTYo1oXDW9arHKDWLILlsqXp3uCS0RZGZJjk5GREREaiqqnLbXlVVBYtFuiZLQ0MDVqxYgeeff172OmazGWazvpzuRvfvgod+qxWNlzdAee4LJfjSVMKKlL1RqsouayIlX/VRyhdHSb6CovIaWOuVmcryM9nKnQcbs8f0RVJ7M6atLA7I9bX2gclNT0RRxWlNziVnShTKneFLLPHRkgn9AODFm/sh0ot0+moWQbPHyCdL1OK7DWb0WmHXFygSRiIjIzFo0CCsX78eN910EwDA4XBg/fr1mDp1quSxn376KWw2G+666y7VjQ00s0ZnIvuSRDy9qsQtdNMzCY8vbHJyGUIB/6wUhPomF4bH6njqyz5q4bglJYi44rpKZBGwEmJMMLczSvrL6InU+CjcOywDCzccCFwjLtzM+4al4/q+KSgqr8Hi/5XBpjIlvFaCCI+YpkBMaPcFrsJ7hNHg04mdxcnbs21zV5diZJb0mKBnh0tf4+uEb3rDwHHK1hcrV67ExIkT8c477yA3NxcLFizAJ598gl9//RUpKSm45557kJaWhnnz5rkdd/XVVyMtLQ0rVqxQ3Mj6+nrEx8ejrq4OcXFxio/XmkBKq3p8QQvLTmH8u1tk91s+eQiTkKanPvLPel2pFZ9sO4ozTfJZNmeP6Yt7h2W4VWLmU2ILCVhv3zXQOeCuLbUKZrrVCwYAiyYMwIETZzF/XQCFEehbkPv3A4NhNBjcxggAbcq3+wrXd8v1m/Hl2CX2nkvBOiaEG2JCq9hz1TOs87fi0N7bb78dJ0+exDPPPAOr1YqcnBwUFBQ4nVqPHDkCo9Fd3bdv3z5s2rQJ3333ndLL6ZJAeiPrcaWgteOpXvqoVp0+d/VevLepHLPH9EVirBm28w48lt8Hy4uOuGlXPFeleT07IjcjCfWN5/HZdumslYEgNT4K47JT8fw3e5m1RL6Eg3TW40DAC0iPf1LsJiClxkfhjiu7+dE0Iyy8+3LsEjOrSEGhuW3RStMcbCjWjAQCvWlGCHe01ozoAV+o01M6mHF1706IMUege1IM7s5Ld7PT+9uXQCmTr87Aez+W+9TEwPuCiIVQ6xmpNvu7P29NGIDR/bv48YoXsTs4vL+5XLYeEiA/JniryQlGn4tQG099phkh2AnGDwFQ3m49ONdqidTKxBuqztjcNB7vbSp3rl796UsghtEgnfZ/ySbfCiLARafU+BiT4sRggcYSH4UzTedx1na+zW/+fK58HayRWakBGW8ijAbcOywD720q92pM8NZcqydzrxLCNeEbFcrzEd6GuQYKNe0OtTA8NTkT1MBHGq3Zddwnwo9S5FLC+KsMiAFAtCkCH07KRUJ0cIQP3zrwEjS1CAsi/kYPqdK9HRO8LZIXzEX2Ap3GIVCQMOIDgvVD8Kbdeq97oAR/rTi4C39//c8u3ZpmAgE/mbZrZ8RLf+in6+JzvI/If7b/htPn2AURf/Qp0CtntWOCt0Xygr3IXrgmfCMzjcYEq/ORFu3Wi+Opt/h7xdFgk4/QCUYi2xnRrDLUFmidTM3tjIImm8QYE1rsDpwN4L1z9QNROq1FR0bgXLNv266HlbOaMcHb0hf+Kp3hK/SSxsHfkGZEY4K12qRW7RZKZR9syK1MwhWDgW1Fz+8jJoi0NwtnsfWkoroBD3+0XdB35PS5FozP9V2ZCAOA9uZ2iI8SX69Z4qMwLb+3Kt+Wc812PHZ9b7xxRw6m5ffR9F3T28pZ6Zjgrc+EmuO9KWPhC0JJ08wKaUY0Jlidj4K13b6ApTBeOBJjal3Ni92TdkZgXHYXbD5YLVmcLzYyAu3NJlTVSzs3Lt0snO2Y3+ebXVZMvjoD7/4ovp83vPrH/m2qSnsWvftm13HV5/9wy2EUPZWPCKMBl1raM0dSud5/oWfBoTXXTTAuBADvfSaUHq9XR9dQ0TSzQpoRjQlW56NgbbevEFuZdIyNxPWXdUJijH/keIPI/weChmY7HsvvI1os0O4APt9xXLZKcNWZZozP7QZA3LlxUPdE1DWK+2Dwmrpr+3TGWxMGIik2krEX8qS6rD5dV/VCRe+8+R5ONTQ7NY2jslIxewxbYUVLfBQW3zUQiwXeT565q/fq1jdNDm99JpQcr3f/vlDQNLNCmhGNCdYw12Btty+RWpnYHRz+b/0BvLHet1lI+eRVAHSRg6RbxxhEidQwUaJBSk+OEU1PPntMJv72xW6m80z5eDte+kM//PxUPorKa7D54Eks3FimoCUXuSHLgnvy0hWtPvnvRu1z4TWNdgeHuatLJfeNNhlx77B0XNWrE4b0aJ2YHA7gkY+3t9lXSU0oveGtzwTr8QB86t8XrKkdAgUJIxoTrM5HwdpuXyOWsTLCaMCQHh2ZhJEp1/VEVZ0N/919HA0tbA6dU6/riWG9OrkNYLxg9N+SSnxQeFhZRzSi5qxNk9TrnTtEIa9nR0Fhr6i8BrWNbH4YtY0tzkl3RKYFmw9Wq2qPJc6MhRMGKn6/+e/m4Y/aCgQsJLc3o7DsFDYfPCkr0DS2OPD294fw9veHkBofhdlj+oomFuMn06e+KEFjsx2W+GjnQiIYJkhvi+SxHF9Ydspnjq56Nf3oGcrAqhGeUvDphmbMXR18LyN9ROysKj6GR1cUy+6XEG1inlyB1lDRbU+PEJ0kWDM0ak1sZAQmDu2Ot74/5NV5EqJNWHTnQOfq3hPW+8pjQGuStKh2EYrT1GtV6+ONdQcwf91+Rcck+rmuTsIF85qrw63ev21fZmBlfc/euCMHN+akMV8zlOrKaAFlYPUjYhM4X5tE76sQV8LNacobWP0FlAgiAHBVr2SvMt56IpdZFbiYL0Oq1ktDs91rQQRovR93vrdVdCJU6ofBgZ9glUe1aFW1durwXlhedFiRYOHvujpCUT96N+d4W0tH6nhf+MkFa2oHPUAOrF4i5QA15eMdqGtsDjrno3BymvIGX4UA/1JRIxlayJLdclp+a9jo7DF9mTKncgDmjstyrp79gZiToD9Dq2eP0UYrEGE04Nlxl8MAeUfj1Pgov95nKYIhCZiv8EVysWBN7aAHSBjxgmDP9Ed4h5RQ4A3WepvsYCWVh2DxXQPxaH4f3JiThuQOZubrPvP1Hr/WgxH7Rnx1Xz1preGi3fcp+kzizE7hcPnkIXj11mxd1d0J1wnSF2UsKEWCeshM4wXBnukvVPGnF7uYo1yCl4XeWAYrFpOaEhVzTYN0SK4vEPtG1JSj9/baWrw3LM9kVfExjXuiTVXgcJwgvXWU9YRSJKiHhBEv8LcUTKFi8vjaAVfoGQhNQA4HhzuXbFV9HdbBSs6mrtS/JFBsPljd5n12va/f7anEsp98E0F04kyTpu+N3DPReiJ67PreWPnLUa+FtnCdILX0k6MUCeohYcQLWD/eA1VnUVh2yivhgaJcWpESyMS82LVy0pN7Bq4TkN3BqRICpAYrNcJosGSTXbjxID7b9hueHef+PkcYDahrbEbBnirB4yxxZjSdd6DuXIvqvlVUN2DBugOavjdSz0prATGjUyw2zRiOovIaWOubMPebPahpYNfK0QTpvaOs63koRYI6KLTXC+wODle9vIF5UFErPFCoWCtSwsCITAuuenmD6OqQH3A3zRiuaiBQ8wz4YwB2IcAgcS5vhFGh472FJUpHDYtd+i9233nemjAQRiME77Oc8MW/ExzHiUbBqHlvWJ6VmndDjOWTh7hNpErOHW5jiL+gxeNFWOdvEka8xNcfPi/w+GqSDRbkhIHH8ntj/jr5BGSeAzcL3jwDJUKA0QAsHD8Ao/t3aXMOLYRRu4PD+5vLRRNluZIUaxJdXfPXXTRhgDN0vezEWfzfhoOy52UhMcaEX54eAQDM931tqVVw8B+XnYp//tBau0ZolfpYfh+m/CCs742SZ1VQUomZn+/2yrcoIdqEbbPb5qQReu+CMc+Iv9HSFE5m9VYoz4ifUOJopybOPFSdZJV8qCyx+8s2VzBdd12pVfF98uYZ8PZoFiHAwQGJse7RL6x5C4ZfloJth09L3s8IowH3DsvAe5vKZW3a//vrddh2+DTWllrxZfFxN+dWT+c+u4PDsJc2SPaNPzfLyuf0uRZsOXQKRoOB+b5L2f0HdEsUdVC0iVQW9oTF70tNjglvo2omDUsX/G7E7gcQHBlYA4HW2gytTD/hAgkjGuD64cvVxlAqPIRiqJjSj55FGGBNLLZkcwWuvOB0yoq3zyDCaGAOsfU8B6sgNGTeejeBISk2Ejdmp+KSxBgktTfDEndx4mGxaUe2MyKvZ0fk9eyIp8ZkSk5gCzccYMp8qkQFW1h2Cr1T2jPty98z18HfU9jlhSvPPhSWnWK6Bot/mBKhNTcjCc99LV2LRo7EGBOmDu8t+rvYZEgTZFt87W9GyEPCiEbwH77WwkOohYqp+ehZ71VCtAl1jfKOjEozIGrxDNSeg7XvnmG5NQ3NbaJPXAU+JeGMUiu8gpJKJvOYUhycA9Vn2LKZet6zNbsq8fSqErd7wvfdM623ltEPSr59OcFFDgOAebf0I62GBlDWVH1ASc80RmvhwRdZAn2B3cGhsOwUVhUfQ2HZKcFEUmqTxLHeq0nDMphW30oTPGnxDNSeQ0shs9Il4+morFRsmjEcyycPcSbj2jRjuKLVH/88fcGKn39j8m1JiDG53bN5a0rxyMfb2whnrn13RcvEV0q+fW80manxUbRS1xDKmqoPSDOiMVrHmQdDqBir2UWt7wXrPZ06vBfqGpuxlMF/RMlkoMUzUHsOb0vUC+G6yvNGZe/t6l4K1gRsLecd2FJ2CkN6dsS3JZV454KzqhAchFe4WiW+YnlWvMDJOrF1jI3E3BsvD7oaV8FEKJrCgxHSjGiML1IMS6X+DvQKSao2j+dKVO1Hr+Sejsi0MF1DqcaBfwYpce6+HylxZuZnMCorFQ9ekwGDRycMBuDBazIEzxFhNGD2mExFbZVCy1WeHgbnhmY77lyyFcNeWo+//meX7P5ifddCUxRhNGBctvT+47JTEWE0MNXfSYo1oXDW9RjdvwvVivIhye3Z/LmCxRQerJBmRABvQ7K0TjHMn1Nv1XSV2lq9MWGx3lPfZ0AUE4fkKSipxD9/KG/TLgcH/POHcgzolij4biTGRipvpgxCgoTS915Pg7OSarlSjsbeaIrsDg5f7ayU3OernZV4clRfJk3Zizf3Q2Q7Wi/6koKSSsxZVSK7n9EADOqeyHROCulVBwkjHmgV3uUL4UFvoWJKzS7eCgos99RXZi0xx9uqejZveynBjUfMSc4XGghPQULNe5+bkSSZj0Sv+EqIYjFbuX4Pvli0EOzIJdRzxcEB2w6flh1/KdmZekjsdkGJyYEFXngIVfWqUrOLFiYslnuqtVlLTgPEAXjqixI0S+Ss8MZJTsvJU8hRVu17H2E04O83ZjFdd2C3BLVN1pSOsZE+c/ZWY4bUwjxEKIdlceCJ3PPVev4IN0gzcgEK71KOGrOLv1aDWmqmWFa8pxqaMWTeOrx4cz/BPrBOVP+9MGAprWXCmpqdg7vAxxLhNPPz3ehgNmGIgPA3un8XPPRbraTjaExkBLYfqZVvnB+Ye2OWz75ftWZIvWk8wwE1ztdSz5fmD+8hYeQCoZrp1JeoNbvwgsKWQ6cuJJ3ikNcjGUM0vq9aDfLsuT5aRE02rBPVB4WH8UHhYTfVLovpaeH41tTs60qtWPHLUTTY7EzXYxmUa8+14M4lW0XVzbNGZyL7ksQ2uT3am9vhrO08zjULt+Wa3sn44UA1Uzu1YPLV6Rjd33caB6rYGjwoMX2yPDeaP7yHzDQXoPAu5XhjdllbasUTn+7Ewo0HsXBjGe5cshVXvbxBl6pMpWYSoVwpLNETrnjmxZCLxOEjLv42JhMdzOJrDH6FxrdPyftcWdeEhz/ajjW7jrf5bXT/VPz8VL7T3PDhfbkwRYj31gBgf9UZZ70UVmJMEYr2d2X4ZWyRVmph/R4AyObkIXyL0m9aznxM84f3kDBygVDLdOov1Phn+Nu2ypKQTQolgoSY74fURCV1Ll5w4CNxPJvOR+Lw96y1jLx4ZIln+9S8z1OX78CaXW2fEa+JMrcz4tGVO3Baou4Kh9YIGKW1WR76fz0UxC+544uJwPPdGpFpkfwegNbif+Pf3YJHVxRj/LtbdCuEhzKs3zRrgjmaP7xHlZlm0aJFeOWVV2C1WpGdnY0333wTubm5ovvX1tbiqaeewueff46amhp0794dCxYswOjRo1U3XGtIxaoeJf4Z/ratauHd7momYUXI90NJUUWeyrombDl0ijkSR+kKjcUfxRMHBzzy8XYsNrYdpJVEKCglNT4KU4f3xrnm83j3x7aCmRxaTwRS79amGcPbfA9rS61U/0QnSJk+eabl98bU4b2ZxiGaP7xHsWZk5cqVmD59OubMmYPt27cjOzsbI0eOxIkTJwT3b25uxogRI1BRUYHPPvsM+/btw7vvvou0tDTB/QOFGpODtyvuUII1csifqZe11MDwgkQSY86PDwoPC656+eiJ2WP6Ml+7sOwU8z1TukJTo7Hh8TRHqYlQUMLsMZlYW2oV1BBJoaRkAus3Lfdurb1QHZr/HgCoKoVA+A4xrW5qfBQW3zUQj+b3YV4Q+SLZZbihWDPy+uuvY/LkyZg0aRIAYPHixVi9ejWWLl2KmTNnttl/6dKlqKmpwU8//QSTqdU+nJ6e7l2rfYSSSA+KJ1eHv2yrvtDAjMpKxfDLUjBk3jrm3BpCq14lVXyB1qJxLJw404Tf9+/CtEIb1D0RhWWnnCv3RRMG4m9f7lZkNvF0yPNlengAiI824YnPdioSdpRMBKzftJp3ixwc9YmWUXeUN8Y7FAkjzc3N2LZtG2bNmuXcZjQakZ+fj8LCQsFjvvrqK+Tl5WHKlClYtWoVOnXqhAkTJmDGjBmIiBB2RrPZbLDZLtq96+vrlTTTK1heTio3rR5/2VZ9NfhHtjPixZv7OU02chOj2OSkpH+JMezpqlkib8Zlp+L/vbLRfcCMM4PjlK/KXYVGXzvnFR6qVizssE4ESr5pNe8WOTjqFy1Dq/WYKTtYUGSmqa6uht1uR0pKitv2lJQUWK1WwWMOHTqEzz77DHa7HWvWrMHs2bPx2muv4e9//7vodebNm4f4+HjnX9euXZU002ukTA5qK88SrfirCrEvB38x9a4YQqan3IwkJESzRZIkxUYiKVZ8X897JuVU/OA1GfjnD+VtzQv1NtQ1nmdqjyuuQhWrgNUxNhJvTRigKLqoFba9p17XU1ECMaXftJp3ixwcw4dQT3bpK3yeZ8ThcKBz58745z//iYiICAwaNAjHjh3DK6+8gjlz5ggeM2vWLEyfPt357/r6er8LJGKQutU7/FWF2NeDv+sK6L8llfig8LDsMa6TU4TRgEnDMjB/3X7Z415Ys1fWLOR5z4RWaIO6J+L/vbJRE58OIYc8FmdYvvhbZDsjjEaDpAOh57XyenbEwo0HZds2rFcnRd+e0m+a9Z2pPmPDquJjzntPDo4EIY4iYSQ5ORkRERGoqqpy215VVQWLRTiGPzU1FSaTyc0k07dvX1itVjQ3NyMysq1DoNlshtnMblP3J6Ru9R5/2Fb94d3uqt5lEUaSY81ufhp/urYnlv1ULuun4ZpITAipir+uk7KcIywrYkKj0uJvLNFFrtca0qOjT56pLyKQjAZg7uq9zn+nxkdhXHYq/vlDObMQTgXX9AE9B/+gSBiJjIzEoEGDsH79etx0000AWjUf69evx9SpUwWPGTZsGD7++GM4HA4Yja2D0P79+5GamiooiOgdUrdqg69tq/7SwABsgk98jAmPf7oT1np358jbr7hEMpU6C66VYKXQSkCWEhqVCpqu78G6Uiu+KD7mpgXyPM4Xz1RtBJKUVsfTSmuta8I/fyjHg9dk4KudleQgHySs2XX8Qmbhi+8kPQffYOAUeq2tXLkSEydOxDvvvIPc3FwsWLAAn3zyCX799VekpKTgnnvuQVpaGubNmwcAOHr0KC6//HJMnDgRf/7zn3HgwAHcd999+Mtf/oKnnnqK6Zr19fWIj49HXV0d4uLilPdSQ+wODle9vEF2dbZpxnCSnl0I1OrCX4M67wAJtJ0kxT4wvvdCE5TSarjLJw+RNU1sPlCNO5dsZT6nazs5APcNS8eITAvTs1P7vFmO03qCUPtNC71bUjWC+PP876/XYdvh04od5Pk9yEHeP8xbUyq6UDCAngMrrPO3Yp+R22+/HSdPnsQzzzwDq9WKnJwcFBQUOJ1ajxw54tSAAEDXrl3x7bffYtq0aejfvz/S0tLw6KOPYsaMGSq6FXj8ueIOFQK5yvOXd7uYRiAlzoym8w5BUwwfafPVzso2E5S1vgnTVhYzX59J66Gyy0mxkXjh5ixFz0pthILccQUllZi72t2HJik2ErPHqH+X1H7Tnu9W9Rmbm2nGE973RKoUvd4KroWriWLNrkpJjSWfHZkK32mHYs1IINCTZoSH1KhshNIqj2Vg9tzHwXG48z15bYSnZqOw7BTGv7uFuW0smpFVxcfw6Ipi5nPyzL8tGzcPvKTNdqH7AUDzyYu/zrpSK5Zsrmjzu1bvkrffNOv9feOOHNyYI5z0kfW5szxvKVje5XAd4+wODle+sE7WVwvw/jmEAz7TjBCtUDy5PHpb5XmD1MAs9R6sKj7GdP7NB6vdjleSpp01FFqtH5MlPrrNNqH7wRe9c9UCeTt5CV3HE63eJc9vOrm9GeCA6gYbCstOSX7fdgeH6jPiNYFckXoO/nCQZxEyxBYRfLFEJanSg42i8homQQSgQAUtIWHEC7RMlqMFelOphkoYtFRCrIc/2o6EGJPoBMwqALiGrPLHs9TDMYDdLMgLOEoiaoQEnTW7juORj3e02VfIFOVNIkAldW60epf4b7qgpBJPfLqTSSvAIjABbNE+vnaQZ0nuNiLTIpvWf/66A1hedBTPjgs9LYkSAYMCFbSDqvYGGWK1MwpKKnVXDTQUwqBZEmJ5TsKutW+UVPz1PB5oNT2kiiRXY60oysP7RrC2RUjQWbOrElOXtxVExPBMGsZa+0VtnRuxd4m/7hc7jmHJj4fwxfbfRK+vpKaR2L5CcAAGdU+U3MeXSQHl3mUOwMzPd2PppkNM/bHW+6bKdqBhFTCSYk2UF0ZDSDMSRIipV/n8BXpLTx8KYdBq6q14mg3kwkCljt80Y7jTdGCtb0LNWRuSYiNhiY9WpfniHW1nfi5dhyYxxoR5t/RrE276yMfslYtd+1NZ14SFGw5ixc9HmLQNauvcCL1LBSWVeParPbDWtzWjeF5fiWkREC9+J8Y3uyqx6WA1XvK4tzy+dJBnuae151rwwppfFZ2XxTzmb62tN9dj1SD+/caskDRTBQoSRoIEKRuumNd3oP0yQqGstlqtjavZgCW5l9TxeT07amrG4n0jFm44gGWbK1DbeFEoSYg2YdKw9Db+AHYHh2e/2uPVdYWyzYoJzGrue0JM25VqQUklHpYwdVV6XF9pVWk1AlPtuRbJRYKvkgL6QgPJYh7ztyOst9dzFQjFBM2HrsnA6P5dNGoxAZAwEhR4U5o9kH4ZoRAG7a3Whp8APJN7CUWFCLH5YLVPVpERRgMeze+DqcN7M60gF244KKhZ8BYtCgnyTBqa0UaAmvn5bqY28Nf3l2lRLjTUFw7yvtRAit0PfxcV1ep6YgJhx9hIzL0xC6P7h5afjB4gYSQI0KI0e6D8MoK9rLaSqBYhXCeACKMBuRlJmP5JMfPxCzcexH+2/+ZVQi+pCY3FCbugpJKpho5ahARmpfc9IcaEqcN7uW3bUnZKNtU+D399f5oW5RYJWjvIe/suSyF0P/wdTaf19Shi0r+QMBIEaCFIBNIvI5g/apbU30KImaDUCJaeqzpWe7iQujop1oS/35jFrGLmB3i1KLlnnoUEldz3SUPT8c2u4273o/BQtaK2njjThN/37yJrWkyKjYS1rhGd46JgiTOjqt6menL35yJB7bsshZSp1d/RdL64nt4iJkMZEkZE0FOYrDeChF78MoL5oxbT7sSaI9BgsysyQamZfFxXdQ4HMHe1h5Ypzozxud2QnhzrfFfXlloF1dU1DS145OMdeOi3WswandnmWkJJ21iFJ4MBiItqh7rG885t8dEm5PftjM+2y+db8XzPR2WlYtGEgRdSvwvnfeBzm8xfd8C5jfcPUJpytnOHKNkJmwNwqqEZ0z7Z6bw+/3y81Zz5AzX+S7cOTBN8fnKmVn9H04VC9F44Q8KIAHrLPMiqXg1Wv4xgYFRWKhwOuE2MDTa7YKIvKROU2smHX9UJRbNY621uk7ElLgpN5+2S78o7P5Qj+5JEN9u3YCKzaBNzGxeNH4iRWRYs3HAQyzaXo7axBbWNLfhs+zHZGj1CAnNr6vdSN0EkMcaEe/K6o0en9qioPocF6/YLOnX/6aPtePT63sxtdw2XVTJh11147vEeuWbkCOQigddUbjl0ClP+vd3NgdkVvo0v35qN/MwUxaZWf0fThUL0XjhD6eA90Gv6cqlCbIBwsbVwSN3sL+Tei8fy+yA9OUZWi8YXZfPWB0gLOsZGouipfEQYDYoSjAkxLb83Hs3vo/g8Yt+V3P1eNGEA5q7eK3kfU+OjcK75vJumRozFAt81ryWy1jdh7jd7RAsX8pP2q7dmo7rBhs4donC6wYa/fVkiKKAEeixxRW5ccW2jUm2xv4uKUhFTfcI6f5Mw4oLcRBHol1lOY6Mn01IoofV7sWaXunwdvmD55CHIzUjySkBKvdB3AIrPIyQw2x0chr20XjR6xwAgkbGq8bT83m5aI08SYkyiOT941NaLsTs4Ny0Rj94WCb7UBCsRdrTA39cj5KHaNCrQe/pyOUfQYPbL0DOs78WWQ6dgNBhkhcEDJ876sLXKOHGmSXW0lqcZsLDslKLzxEZG4B+39MfQ3slu2+XCiDmASRABgG5JMVh810A8+1UprPXu5qdJwzIwdXgvWQFSrS9Ca/h0b0wd3kvXiwRfOpj7O5ou2KP3whkSRlwIBgcoEjj8D+vz9rS/i636l20WL03ubzp3iGLuX0K0ya1/ngO80u+iodmOu5cVud0nrcOIaxqacf/AHl5Ntt76IgTDN+vLNvo7mi6Yo/fCGRJGXCAHKEII1uft6QgolGipqLxG1GHQ3xgNrbVSth0+zbT/ogkDYTSKa36SY82q2sHfJ94PREuS2re2yZvJNhQyCQcafwtkwSAAEu6QMOICDTqEEGqTRbmG5HYwm1DdYMOBKv2YaBwcsO3waeb3fkjPjtKrS5ULT/4+tUYqaSuoWeK8XziEQiZhgtA7VLXXBX7QAdqOqzTohC9S74UcvD/JnUu24tEVxVi48aDm7fNESRtPnGnS7L2vPqs+XbwSPxBW1Fa3FYL3RbB4VFC2KKycTBCEMCSMeECDDiGE2HvR3ux/5aIBrWG582/LxrT8Pm1W/5b4KEzL78N0Lt4EpcV7rzfzpdYLh1FZqdg0YziWTx6CN+7IwfLJQ7BpxnAaEwhCAyi0VwQKkyWEWLPruE/MCUowQD7/AwBVORe8ee/l8jywkBQbidMNzaLHp8ZHgeM4yRTsRgOwcPxAKmZGEDqA8owQhMZ4mxhMC5RMtIHIuSB2TTl44Wj2mExM+Vi6zQAkr/HWhAFU3l0CWmgR/oR1/iYzDUEwIFUR1J84OCAxNpJp30CYHMWumRofhYeuyYAB0n4po/vLt1nqGovvGkiCiAQFJZW46uUNGP/uFjy6ohjj392Cq17egIKSykA3jQhzSDNCEAywZuH0B2/ckYMbc9KY9w/ESljsmqzZPlnaTCt8Zei11AUR2lAGVoLQEKUJvZJiI+FwOFDXeF7UZ8NgaNV0KEWpo6g3ORfUTvhi12RNSMXSZsolwY6UZs81BH1EpoUEOiIgkDBCEAwoFQBcnTDFclNMvjoD//yhNRsri0yiNM+Nt5oDX9UsISHC/+i91AVBkDBCEAwoTXzGrzYTYkwwtzO61VpxTaM+oFsiU6l6pXluvBUkxFT6Qlllg41wNO8EQ6kLIrwhYYQgGJDKwikGB+D0uRb8+4HBogX0hMwWpxtsmLt6r+pCX94KEqGs0vdlhVo9Q6UuCL1DwghBMCJWEVSO6rM2SYdTIbPFyKxUVat3LQSJUFXph7K2Rw4qdUHoHQrtJQgFuGbhnHpdT6Zj1Kw2eQHlxpw05MnVhHFBiSAhRiiq9OWENKBVSLOr8Sj2E3YHh8KyU1hVfAyFZacUtZVKXRB6hzQjBKEQXlDIzUjCf7Yf09VqUwtBIhRV+sGu7dHCvCSm2VNiAiQIX0HCCEGoRI/VXLUQJEJRpR/M2h4tzUusodUE4W/ITEMQXqC3woq8ICE2tRggX802FFX6wart8YV5Sa0JkCB8CWlGCMJL9LTa1EpbE2oq/WDV9gS7eYkgWFGlGVm0aBHS09MRFRWFwYMHo6ioSHTf999/HwaDwe0vKkpfqw+C8BY9rTa10ta4Ouu+cUcOlk8egk0zhgedIAIEr7YnmM1LBKEExZqRlStXYvr06Vi8eDEGDx6MBQsWYOTIkdi3bx86d+4seExcXBz27dvn/LfBoK8PniBCDa20NaGULTUYtT3Bal4iCKUoFkZef/11TJ48GZMmTQIALF68GKtXr8bSpUsxc+ZMwWMMBgMsFot3LSUIQhGhJEhohZ5MaiwEq3mJIJSiyEzT3NyMbdu2IT8//+IJjEbk5+ejsLBQ9LizZ8+ie/fu6Nq1K2688Ubs2bNH8jo2mw319fVufwRBEFqgJ5OaHMFqXiIIpSgSRqqrq2G325GSkuK2PSUlBVarVfCYSy+9FEuXLsWqVavw0UcfweFwYOjQofjtt99ErzNv3jzEx8c7/7p27aqkmQRBECGD3iK2CMIX+DyaJi8vD3l5ec5/Dx06FH379sU777yDuXPnCh4za9YsTJ8+3fnv+vp6EkgIgghbgs28RBBKUSSMJCcnIyIiAlVVVW7bq6qqmH1CTCYTBgwYgIMHD4ruYzabYTablTSNIAgipCEfICKUUWSmiYyMxKBBg7B+/XrnNofDgfXr17tpP6Sw2+3YvXs3UlNJtUgQBEEQhAozzfTp0zFx4kRcccUVyM3NxYIFC9DQ0OCMrrnnnnuQlpaGefPmAQCef/55DBkyBL169UJtbS1eeeUVHD58GA888IC2PSEIgiAIIihRLIzcfvvtOHnyJJ555hlYrVbk5OSgoKDA6dR65MgRGI0XFS6nT5/G5MmTYbVakZiYiEGDBuGnn35CZmamdr0gCIIgCCJoMXAcp9+a2Reor69HfHw86urqEBcXF+jmEARBEATBAOv8TYXyCIIgCIIIKCSMEARBEAQRUEgYIQiCIAgioJAwQhAEQRBEQCFhhCAIgiCIgELCCEEQBEEQAYWEEYIgCIIgAgoJIwRBEARBBBQSRgiCIAiCCCgkjBAEQRAEEVBIGCEIgiAIIqCQMEIQBEEQREAhYYQgCIIgiIBCwghBEARBEAGFhBGCIAiCIAIKCSMEQRAEQQQUEkYIgiAIgggoJIwQBEEQBBFQSBghCIIgCCKgkDBCEARBEERAIWGEIAiCIIiAQsIIQRAEQRABhYQRgiAIgiACCgkjBEEQBEEEFBJGCIIgCIIIKCSMEARBEAQRUEgYIQiCIAgioJAwQhAEQRBEQCFhhCAIgiCIgELCCEEQBEEQAYWEEYIgCIIgAooqYWTRokVIT09HVFQUBg8ejKKiIqbjVqxYAYPBgJtuuknNZQmCIAiCCEEUCyMrV67E9OnTMWfOHGzfvh3Z2dkYOXIkTpw4IXlcRUUFnnjiCVx99dWqG0sQBEEQROihWBh5/fXXMXnyZEyaNAmZmZlYvHgxYmJisHTpUtFj7HY77rzzTjz33HPo0aOHVw0mCIIgCCK0UCSMNDc3Y9u2bcjPz794AqMR+fn5KCwsFD3u+eefR+fOnXH//fczXcdms6G+vt7tjyAIgiCI0ESRMFJdXQ273Y6UlBS37SkpKbBarYLHbNq0CUuWLMG7777LfJ158+YhPj7e+de1a1clzSQIgiAIIojwaTTNmTNncPfdd+Pdd99FcnIy83GzZs1CXV2d8+/o0aM+bCVBEARBEIGknZKdk5OTERERgaqqKrftVVVVsFgsbfYvKytDRUUFxo4d69zmcDhaL9yuHfbt24eePXu2Oc5sNsNsNitpGkEQBEEQQYoizUhkZCQGDRqE9evXO7c5HA6sX78eeXl5bfa/7LLLsHv3bhQXFzv/xo0bh+uuuw7FxcVkfiEIgiAIQplmBACmT5+OiRMn4oorrkBubi4WLFiAhoYGTJo0CQBwzz33IC0tDfPmzUNUVBSysrLcjk9ISACANtsJgiAIgghPFAsjt99+O06ePIlnnnkGVqsVOTk5KCgocDq1HjlyBEYjJXYlCIIgCIINA8dxXKAbIUd9fT3i4+NRV1eHuLi4QDeHIAiCIAgGWOdvUmEQBEEQBBFQSBghCIIgCCKgkDBCEARBEERAIWGEIAiCIIiAQsIIQRAEQRABhYQRgiAIgiACCgkjBEEQBEEEFBJGCIIgCIIIKCSMEARBEAQRUEgYIQiCIAgioJAwQhAEQRBEQCFhhCAIgiCIgELCCEEQBEEQAYWEEYIgCIIgAgoJIwRBEARBBBQSRgiCIAiCCCgkjBAEQRAEEVBIGCEIgiAIIqCQMEIQBEEQREAhYYQgCIIgiIBCwghBEARBEAGFhBGCIAiCIAIKCSMEQRAEQQQUEkYIgiAIgggoJIwQBEEQBBFQSBghCIIgCCKgkDBCEARBEERAIWGEIAiCIIiAQsIIQRAEQRABhYQRgiAIgiACCgkjBEEQBEEEFBJGCIIgCIIIKKqEkUWLFiE9PR1RUVEYPHgwioqKRPf9/PPPccUVVyAhIQGxsbHIycnBhx9+qLrBBEEQBEGEFoqFkZUrV2L69OmYM2cOtm/fjuzsbIwcORInTpwQ3D8pKQlPPfUUCgsLsWvXLkyaNAmTJk3Ct99+63XjCYIgCIIIfgwcx3FKDhg8eDCuvPJKLFy4EADgcDjQtWtX/PnPf8bMmTOZzjFw4ECMGTMGc+fOZdq/vr4e8fHxqKurQ1xcnJLmEgRBaI7dwaGovAYnzjShc4co5GYkIcJoCHSzCEJ3sM7f7ZSctLm5Gdu2bcOsWbOc24xGI/Lz81FYWCh7PMdx2LBhA/bt24eXX35ZdD+bzQabzeb8d319vZJmEgRB+IyCkko893UpKuuanNtS46MwZ2wmRmWlBrBlBBG8KDLTVFdXw263IyUlxW17SkoKrFar6HF1dXVo3749IiMjMWbMGLz55psYMWKE6P7z5s1DfHy8869r165KmkkQBOETCkoq8aePtrsJIgBgrWvCnz7ajoKSygC1jCCCG79E03To0AHFxcX4+eef8cILL2D69On4/vvvRfefNWsW6urqnH9Hjx71RzMJgiBEsTs4PPd1KYTs2vy2574uhd2hyPJNEAQUmmmSk5MRERGBqqoqt+1VVVWwWCyixxmNRvTq1QsAkJOTg71792LevHm49tprBfc3m80wm81KmkYQBOFTispr2mhEXOEAVNY1oai8Bnk9O/qvYQQRAijSjERGRmLQoEFYv369c5vD4cD69euRl5fHfB6Hw+HmE0IQBKF3TpwRF0TU7EcQxEUUaUYAYPr06Zg4cSKuuOIK5ObmYsGCBWhoaMCkSZMAAPfccw/S0tIwb948AK3+H1dccQV69uwJm82GNWvW4MMPP8Tbb7+tbU8IgiB8SOcOUZruRxDERRQLI7fffjtOnjyJZ555BlarFTk5OSgoKHA6tR45cgRG40WFS0NDAx555BH89ttviI6OxmWXXYaPPvoIt99+u3a9IAiC8DG5GUlIjY+Cta5J0G/EAMAS3xrmSxCEMhTnGQkElGeEIAg9wEfTAHATSPgMI2/fNZDCewnCBdb5m2rTEARBMDIqKxVv3zUQlnh3U4wlPooEEYLwAsVmGoIgiHBmVFYqRmRaKAMrQWgICSMEQRAKiTAaKHyXIDSEzDQEQRAEQQQUEkYIgiAIgggoJIwQBEEQBBFQSBghCIIgCCKgkDBCEARBEERAIWGEIAiCIIiAQsIIQRAEQRABhYQRgiAIgiACCgkjBEEQBEEElKDIwMrX8quvrw9wSwiCIAiCYIWft+Vq8gaFMHLmzBkAQNeuXQPcEoIgCIIglHLmzBnEx8eL/m7g5MQVHeBwOHD8+HF06NABBoP+ilHV19eja9euOHr0qGSJ5GCG+hg6hEM/qY+hQzj0M5T7yHEczpw5gy5dusBoFPcMCQrNiNFoxCWXXBLoZsgSFxcXci+SJ9TH0CEc+kl9DB3CoZ+h2kcpjQgPObASBEEQBBFQSBghCIIgCCKgkDCiAWazGXPmzIHZbA50U3wG9TF0CId+Uh9Dh3DoZzj0UY6gcGAlCIIgCCJ0Ic0IQRAEQRABhYQRgiAIgiACCgkjBEEQBEEEFBJGCIIgCIIIKCEvjKSnp8NgMLT5mzJlCgDAarXi7rvvhsViQWxsLAYOHIj//Oc/bucYN24cunXrhqioKKSmpuLuu+/G8ePH3fbZtWsXrr76akRFRaFr1674xz/+0aYtn376KS677DJERUWhX79+WLNmjdvvHMfhmWeeQWpqKqKjo5Gfn48DBw74rZ88NpsNOTk5MBgMKC4u1k0/teij0DleeumlkOojAKxevRqDBw9GdHQ0EhMTcdNNN7n9fuTIEYwZMwYxMTHo3Lkz/vrXv+L8+fNu+3z//fcYOHAgzGYzevXqhffff7/NdRYtWoT09HRERUVh8ODBKCoqku2jFv38/vvvBY83GAz4+eefnfsF+7Pcv38/brzxRiQnJyMuLg5XXXUVNm7c6LZPIJ+lFn3cvn07RowYgYSEBHTs2BEPPvggzp49q5s+svSzrKwMN998Mzp16oS4uDjcdtttqKqqcjtHTU0N7rzzTsTFxSEhIQH3339/m34Geh4JKFyIc+LECa6ystL5t3btWg4At3HjRo7jOG7EiBHclVdeyW3dupUrKyvj5s6dyxmNRm779u3Oc7z++utcYWEhV1FRwW3evJnLy8vj8vLynL/X1dVxKSkp3J133smVlJRwy5cv56Kjo7l33nnHuc/mzZu5iIgI7h//+AdXWlrKPf3005zJZOJ2797t3Oell17i4uPjuS+//JLbuXMnN27cOC4jI4NrbGz0Sz95/vKXv3A33HADB4DbsWOHbvqpRR+7d+/OPf/8827nOXv2bEj18bPPPuMSExO5t99+m9u3bx+3Z88ebuXKlc7fz58/z2VlZXH5+fncjh07uDVr1nDJycncrFmznPscOnSIi4mJ4aZPn86VlpZyb775JhcREcEVFBQ491mxYgUXGRnJLV26lNuzZw83efJkLiEhgauqqpLsoxb9tNlsbsdXVlZyDzzwAJeRkcE5HI6QeZa9e/fmRo8eze3cuZPbv38/98gjj3AxMTFcZWWlLp6lt308duwYl5iYyD388MPcr7/+yhUVFXFDhw7l/vCHPzivEeg+yvXz7NmzXI8ePbibb76Z27VrF7dr1y7uxhtv5K688krObrc7zzFq1CguOzub27JlC/fjjz9yvXr14saPH+/8PdDva6AJeWHEk0cffZTr2bOnc8CKjY3lPvjgA7d9kpKSuHfffVf0HKtWreIMBgPX3NzMcRzHvfXWW1xiYiJns9mc+8yYMYO79NJLnf++7bbbuDFjxridZ/DgwdxDDz3EcRzHORwOzmKxcK+88orz99raWs5sNnPLly/3Wz/XrFnDXXbZZdyePXvaCCN666eaPnbv3p2bP3++6DmDvY8tLS1cWloa995774mec82aNZzRaOSsVqtz29tvv83FxcU5+/3kk09yl19+udtxt99+Ozdy5Ejnv3Nzc7kpU6Y4/22327kuXbpw8+bNU9RHNf30pLm5mevUqRP3/PPPO7cF+7M8efIkB4D74YcfnL/X19dzALi1a9dyHKe/Z6m0j++88w7XuXNnt0l7165dHADuwIEDuuyjZz+//fZbzmg0cnV1dc7fa2trOYPB4HxOpaWlHADu559/du7z3//+lzMYDNyxY8c4jtPf++pvQt5M40pzczM++ugj3Hfffc6Ce0OHDsXKlStRU1MDh8OBFStWoKmpCddee63gOWpqavDvf/8bQ4cOhclkAgAUFhbimmuuQWRkpHO/kSNHYt++fTh9+rRzn/z8fLdzjRw5EoWFhQCA8vJyWK1Wt33i4+MxePBg5z6+7mdVVRUmT56MDz/8EDExMW3Oq6d+evMsX3rpJXTs2BEDBgzAK6+84qbuDfY+bt++HceOHYPRaMSAAQOQmpqKG264ASUlJW597NevH1JSUtzaX19fjz179jD1sbm5Gdu2bXPbx2g0Ij8/32/vqytfffUVTp06hUmTJrn1M5ifZceOHXHppZfigw8+QENDA86fP4933nkHnTt3xqBBg5zt18uzVNNHm82GyMhItwJq0dHRAIBNmzbpro9C/bTZbDAYDG4Jy6KiomA0Gt36kJCQgCuuuMK5T35+PoxGI7Zu3ercRy/vayAIK2Hkyy+/RG1tLe69917ntk8++QQtLS3o2LEjzGYzHnroIXzxxRfo1auX27EzZsxAbGwsOnbsiCNHjmDVqlXO36xWq9uHAsD5b6vVKrmP6++uxwnt48t+chyHe++9Fw8//LDbB+OKnvqp9ln+5S9/wYoVK7Bx40Y89NBDePHFF/Hkk0+GTB8PHToEAHj22Wfx9NNP45tvvkFiYiKuvfZa1NTUeN3H+vp6NDY2orq6Gna7PWDvqydLlizByJEj3QpqBvuzNBgMWLduHXbs2IEOHTogKioKr7/+OgoKCpCYmOh1H7V+lmr6OHz4cFitVrzyyitobm7G6dOnMXPmTABAZWWl7voo1M8hQ4YgNjYWM2bMwLlz59DQ0IAnnngCdrvdrQ+dO3d2O0+7du2QlJQk2weWfvpiHvE3YSWMLFmyBDfccAO6dOni3DZ79mzU1tZi3bp1+OWXXzB9+nTcdttt2L17t9uxf/3rX7Fjxw589913iIiIwD333ANOp8lr1fTzzTffxJkzZzBr1qxANVsRap/l9OnTce2116J///54+OGH8dprr+HNN9+EzWYLRDckUdNHh8MBAHjqqafwhz/8AYMGDcKyZctgMBjw6aefBqQfcnjzXQLAb7/9hm+//Rb333+/P5utCDV95DgOU6ZMQefOnfHjjz+iqKgIN910E8aOHeuc5PSEmj5efvnl+Ne//oXXXnsNMTExsFgsyMjIQEpKimS5+UDi2c9OnTrh008/xddff4327dsjPj4etbW1GDhwoG77oEfaBboB/uLw4cNYt24dPv/8c+e2srIyLFy4ECUlJbj88ssBANnZ2fjxxx+xaNEiLF682LlvcnIykpOT0adPH/Tt2xddu3bFli1bkJeXB4vF0sZzmv+3xWJx/ldoH9ff+W2pqalu++Tk5Pi8nxs2bEBhYWGb2ghXXHEF7rzzTvzrX//STT+9fZauDB48GOfPn0dFRQUuvfTSoO8jf73MzEzncWazGT169MCRI0ec7fOMImDtY1xcHKKjoxEREYGIiAjJ++DLfrqybNkydOzYEePGjXPbHuzPcsOGDfjmm29w+vRpZ1n5t956C2vXrsW//vUvzJw5UzfP0pvnOGHCBEyYMAFVVVWIjY2FwWDA66+/jh49ejjbr4c+ivUTAH73u9+hrKwM1dXVaNeuHRISEmCxWNz6cOLECbdjzp8/j5qaGtk+sPRT63kkEISN2LZs2TJ07twZY8aMcW47d+4cALSRXiMiIpwrTCH43/jVdF5eHn744Qe0tLQ491m7di0uvfRSpzo1Ly8P69evdzvP2rVrkZeXBwDIyMiAxWJx26e+vh5bt2517uPLfv7f//0fdu7cieLiYhQXFzvDxVauXIkXXnhBV/3U8lkWFxfDaDQ6VajB3sdBgwbBbDZj3759zt9bWlpQUVGB7t27O9u/e/dut8Fx7dq1iIuLcwoxcn2MjIzEoEGD3PZxOBxYv369X95XHo7jsGzZMtxzzz1OHy6eYH+WYvsYjUbnPnp5llp8kykpKWjfvj1WrlyJqKgojBgxQld9FOunK8nJyUhISMCGDRtw4sQJp4Ccl5eH2tpabNu2zbnvhg0b4HA4MHjwYOc+enhfA0Zg/Wf9g91u57p168bNmDHDbXtzczPXq1cv7uqrr+a2bt3KHTx4kHv11Vc5g8HArV69muM4jtuyZQv35ptvcjt27OAqKiq49evXc0OHDuV69uzJNTU1cRzX6q2ckpLC3X333VxJSQm3YsUKLiYmpk1IVrt27bhXX32V27t3LzdnzhzBkKyEhARu1apVzvAwJSFZ3vTTk/Ly8jbRNHropzd9/Omnn7j58+dzxcXFXFlZGffRRx9xnTp14u65556Q6SPHtXr6p6Wlcd9++y3366+/cvfffz/XuXNnrqamhuO4i6GSv/vd77ji4mKuoKCA69Spk2Co5F//+ldu79693KJFiwRDJc1mM/f+++9zpaWl3IMPPsglJCS4RT34sp8cx3Hr1q3jAHB79+5tc/5gf5YnT57kOnbsyN1yyy1ccXExt2/fPu6JJ57gTCYTV1xczHGcPp6lt8/xzTff5LZt28bt27ePW7hwIRcdHc298cYbzt/10EepfnIcxy1dupQrLCzkDh48yH344YdcUlISN336dLd9Ro0axQ0YMIDbunUrt2nTJq53795uob16eF8DSVgII99++y0HgNu3b1+b3/bv38/dcsstXOfOnbmYmBiuf//+bqFou3bt4q677jouKSmJM5vNXHp6Ovfwww9zv/32m9t5du7cyV111VWc2Wzm0tLSuJdeeqnNtT755BOuT58+XGRkJHf55Ze3GVgdDgc3e/ZsLiUlhTObzdz1118v2GZf9NMTIWFED/30po/btm3jBg8ezMXHx3NRUVFc3759uRdffNEpVIZCHzmudRJ4/PHHuc6dO3MdOnTg8vPzuZKSErd9KioquBtuuIGLjo7mkpOTuccff5xraWlx22fjxo1cTk4OFxkZyfXo0YNbtmxZm/a8+eabXLdu3bjIyEguNzeX27JlC1Mftegnx3Hc+PHjuaFDh4peI9if5c8//8z97ne/45KSkrgOHTpwQ4YM4dasWeO2T6Cfpbd9vPvuu7mkpCQuMjJS9DkHuo9y/ZwxYwaXkpLCmUwmrnfv3txrr73mDG/mOXXqFDd+/Hiuffv2XFxcHDdp0iTuzJkzbvsE+n0NJAaO06kXJkEQBEEQYUHY+IwQBEEQBKFPSBghCIIgCCKgkDBCEARBEERAIWGEIAiCIIiAQsIIQRAEQRABhYQRgiAIgiACCgkjBEEQBEEEFBJGCIIgCIIIKCSMEARBEAQRUEgYIQiCIAgioJAwQhAEQRBEQCFhhCAIgiCIgPL/ASAp1vdR6w3XAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "and compute current unit usage with these whole-unit, possibly discontig HDs\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"lets plot our unit-snapped HD pops vs. orig pops\")\n",
    "plt.scatter([HDvTruePop[h] for h in popHDlist], [HDvPop[h] for h in popHDlist])\n",
    "plt.axhline(aDP,ls=\"--\")\n",
    "plt.show()\n",
    "print(\"and compute current unit usage with these whole-unit, possibly discontig HDs\")\n",
    "unitUse = [0.]*nUnits\n",
    "for h in popHDlist:\n",
    "    for u in HDunitList[h]:\n",
    "        unitUse[u] += nDistricts * HDwt[h]\n",
    "plt.hist(unitUse,weights=unitPop)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "81a441d0-3a2f-473d-ba3b-0c8b365dfb55",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(unitPop,unitUse)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "ecceb61d-a30b-4337-81cd-75fb7ef961af",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "here are the severely underused units, <0.5 use\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"here are the severely underused units, <0.5 use\")\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] < 0.5:\n",
    "        plotPoly(unitGeom[u])\n",
    "        plotCenter(u,unitGeom[u])\n",
    "plotPoly(mainMAP)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "30de9de6-e831-4cfa-a449-2cc7bf3d330f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "classify these unit HDs by contiguity\n",
      "quick classification: who has contiguity problems?\n",
      "working on HD 0 time is now 0\n",
      "working on HD 700 time is now 84\n",
      "working on HD 1402 time is now 147\n",
      "working on HD 2102 time is now 194\n",
      "working on HD 2802 time is now 281\n",
      "working on HD 3503 time is now 328\n",
      "working on HD 4204 time is now 362\n",
      "working on HD 4906 time is now 405\n",
      "working on HD 5606 time is now 465\n",
      "working on HD 6306 time is now 533\n",
      "working on HD 7006 time is now 594\n",
      "working on HD 7706 time is now 621\n",
      "working on HD 8407 time is now 706\n",
      "out of 8934 total HDs, there were 8934.0 contiguous and 3236.0 complement-contiguous HDs\n",
      "0 HDs had both discontiguity problems, while enclave-only = 5698 and discontig only= 0\n",
      "here are the histograms of the small piece and enclave list lengths, total no = 0 5698\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "And here are the small-HD-piece and small-enclave pops\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"classify these unit HDs by contiguity\") #take from vanillaHD\n",
    "\n",
    "### THIS IS THE \"FIND DISCO\" CODE\n",
    "print(\"quick classification: who has contiguity problems?\")\n",
    "nUnbroken, nNoEnclave, smallPieceLists, enclaveLists, sPgenerator, eLgenerator = 0., 0., list(), list(), list(), list()\n",
    "smallPieceLengths, enclaveLengths = list(), list()\n",
    "doubleTroubleList = list()\n",
    "startTime = time.time()\n",
    "for i,t in enumerate(popHDlist):\n",
    "    if i%700 == 0:\n",
    "        print(\"working on HD\",t,\"time is now\",int(time.time() - startTime) )\n",
    "    unbroken, noEnclave,smallPieceList,enclaveList = enclaveCheck(HDunitList[t], unitNbrs,4) #,6) #6 is high (slow) to try to avoid false enclaves\n",
    "    if unbroken:\n",
    "        nUnbroken +=1\n",
    "    if noEnclave:\n",
    "        nNoEnclave +=1\n",
    "    if not unbroken:\n",
    "        smallPieceLists.append(smallPieceList)\n",
    "        smallPieceLengths.append(len(smallPieceList))\n",
    "        sPgenerator.append(t)\n",
    "    if not noEnclave and unbroken:   #district is contiguous but contains 1+ enclave\n",
    "        enclaveLists.append(enclaveList)\n",
    "        enclaveLengths.append(len(enclaveList))\n",
    "        eLgenerator.append(t)\n",
    "    if not noEnclave and not unbroken:  #extremely discontig (\"broken\") HDs can appear to have enclaves;\n",
    "        doubleTroubleList.append(t)\n",
    "print(\"out of\",len(popHDlist),\"total HDs, there were\",nUnbroken,\"contiguous and\",nNoEnclave,\"complement-contiguous HDs\")\n",
    "print(len(doubleTroubleList),\"HDs had both discontiguity problems, while enclave-only =\",len(eLgenerator),\n",
    "      \"and discontig only=\",len(sPgenerator)-len(doubleTroubleList) )\n",
    "\n",
    "print(\"here are the histograms of the small piece and enclave list lengths, total no =\",\n",
    "      len(smallPieceLists),len(enclaveLists) )\n",
    "plt.hist([s for s in smallPieceLengths],label=\"small piece l units\",histtype='step',\n",
    "         cumulative=True,bins=[0,1,2,3,4,5,6,8,10,12,15,20,25,30,35,40,45,50,60,80,120])\n",
    "plt.hist([e for e in enclaveLengths],label=\"enclave l units\",histtype='step',\n",
    "         cumulative=True,bins=[0,1,2,3,4,5,6,8,10,12,15,20,25,30,35,40,45,50,60,80,120])\n",
    "plt.legend()\n",
    "plt.show()\n",
    "print(\"And here are the small-HD-piece and small-enclave pops\")\n",
    "plt.hist([sum(unitPop[u] for u in s) for s in smallPieceLists],label=\"small piece 1 pop\",histtype='step')\n",
    "plt.hist([sum(unitPop[u] for u in e) for e in enclaveLists],label=\"enclave 1 pop\",histtype='step')\n",
    "plt.legend()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "6421f8ab-a699-4c29-976e-8c8e39d4597a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now, let's fill in all enclaves that won't put us over 865292 district pop vs 786629 target\n",
      "working on enclave-y HD 0 . We have evaluated 0 of 5698 enclavy HDs.Time is now 0\n",
      "working on enclave-y HD 450 . We have evaluated 379 of 5698 enclavy HDs.Time is now 17\n",
      "working on enclave-y HD 911 . We have evaluated 758 of 5698 enclavy HDs.Time is now 33\n",
      "working on enclave-y HD 1512 . We have evaluated 1137 of 5698 enclavy HDs.Time is now 44\n",
      "working on enclave-y HD 2054 . We have evaluated 1516 of 5698 enclavy HDs.Time is now 58\n",
      "working on enclave-y HD 2566 . We have evaluated 1895 of 5698 enclavy HDs.Time is now 78\n",
      "working on enclave-y HD 3129 . We have evaluated 2274 of 5698 enclavy HDs.Time is now 96\n",
      "working on enclave-y HD 3786 . We have evaluated 2653 of 5698 enclavy HDs.Time is now 107\n",
      "working on enclave-y HD 4397 . We have evaluated 3032 of 5698 enclavy HDs.Time is now 113\n",
      "working on enclave-y HD 5048 . We have evaluated 3411 of 5698 enclavy HDs.Time is now 127\n",
      "working on enclave-y HD 5602 . We have evaluated 3790 of 5698 enclavy HDs.Time is now 144\n",
      "working on enclave-y HD 6188 . We have evaluated 4169 of 5698 enclavy HDs.Time is now 163\n",
      "working on enclave-y HD 6695 . We have evaluated 4548 of 5698 enclavy HDs.Time is now 180\n",
      "working on enclave-y HD 7728 . We have evaluated 4927 of 5698 enclavy HDs.Time is now 192\n",
      "working on enclave-y HD 8328 . We have evaluated 5306 of 5698 enclavy HDs.Time is now 215\n",
      "working on enclave-y HD 8922 . We have evaluated 5685 of 5698 enclavy HDs.Time is now 230\n",
      "Out of 5698 HDs with enclaves 5698 had enclaves.\n",
      "Of these, 5543 wouldn't be over 865292 if all enclaves filled, while 155 were too populous\n",
      "here is enclave pop by final pop for those we filled\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#copy enclave fix here.  Will not have any muni-discontig\n",
    "### THIS IS THE \"CANFILL\" CODE  #check if sum of enclave pops small enough to add\n",
    "maxNudgeUpPop = int(0.02 * aDP)\n",
    "maxPostFixPop = int(1.1 * aDP) #wider tolerance here for unit vs. vtd-based, but still Congr'l\n",
    "print(\"Now, let's fill in all enclaves that won't put us over\",int(maxPostFixPop),\"district pop vs\",int(aDP),\"target\")\n",
    "nOrigEnclaves = [0 for t in range(nHDs)]\n",
    "totalEnclavePop = [0. for t in range(nHDs)]\n",
    "tryToFill, canFill, cantFill = list(), list(), list()\n",
    "startTime = time.time()  #takes about xx sec per HD triage\n",
    "        \n",
    "for iii, t in enumerate(eLgenerator):\n",
    "    if iii%(int(len(eLgenerator)/15)) == 0:\n",
    "        print(\"working on enclave-y HD\",t,\". We have evaluated\",iii,\"of\",len(eLgenerator),\"enclavy HDs.Time is now\",int(time.time() - startTime) )\n",
    "    unbroken, noEnclave,smallPieceList,enclaveList = enclaveCheck(HDunitList[t], unitNbrs)\n",
    "    if unbroken and not noEnclave:  #\"and unbroken\" new 1/15 - discontig HDs will usually appear to have enclaves.  We'll fix these in later block\n",
    "        tryToFill.append(t)\n",
    "        enclaveLists = getEnclaveLists(HDunitList[t], unitNbrs)\n",
    "        nOrigEnclaves[t] = len(enclaveLists)\n",
    "        totalEnclavePop[t] = np.sum( [ [np.sum([unitPop[u] for u in eL])] for eL in enclaveLists ] ) \n",
    "        if HDvPop[t] + totalEnclavePop[t] <= maxPostFixPop or totalEnclavePop[t] < maxNudgeUpPop:\n",
    "            canFill.append(t)\n",
    "            for eL in enclaveLists:\n",
    "                HDunitList[t] += eL\n",
    "                HDvPop[t] += np.sum([unitPop[u] for u in eL])\n",
    "        else:\n",
    "            cantFill.append(t)\n",
    "print(\"Out of\",len(eLgenerator),\"HDs with enclaves\",len(tryToFill),\"had enclaves.\")\n",
    "print(\"Of these,\",len(canFill),\"wouldn't be over\",maxPostFixPop,\"if all enclaves filled, while\",len(cantFill),\"were too populous\")\n",
    "plt.scatter([HDvPop[t] for t in canFill],[totalEnclavePop[t] for t in canFill])\n",
    "print(\"here is enclave pop by final pop for those we filled\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "aced004d-abcf-4b9d-8249-332156a1759a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "defining and displaying current unit use after above manipulations; compare to original farther above.\n",
      "current avg use and its sd are 1.01299 0.10508\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"defining and displaying current unit use after above manipulations; compare to original farther above.\")\n",
    "HDweight = HDwt.copy() #nomenclature\n",
    "unitUse = [0. for u in range(nUnits)]\n",
    "for t in range(nHDs):\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += nDistricts * HDweight[t]\n",
    "activeUnitDistro, activeUnitWeights = list(), list()\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] > 0.01:\n",
    "        activeUnitDistro.append(unitUse[u])\n",
    "        activeUnitWeights.append(unitPop[u]/statePop)\n",
    "plt.hist(activeUnitDistro, weights=activeUnitWeights, bins = 20, histtype = \"step\")\n",
    "#plt.show()\n",
    "currAvg, currSD = getWeightedAvgAndSD(activeUnitDistro, activeUnitWeights)\n",
    "print(\"current avg use and its sd are\",r5(currAvg),r5(currSD) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "c06c0980-fad8-4596-bf2f-ad46bd6bb074",
   "metadata": {},
   "outputs": [],
   "source": [
    "savedHDunitList = [HDunitList[t].copy() for t in range(nHDs) ]  #safekeeping"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "id": "80050c17-7680-4ea9-b803-dfc5bc057e5e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#savedHDunitList = [HDunitList[t].copy() for t in range(nHDs) ]  #safekeeping\n",
    "HDunitList = [savedHDunitList[t].copy() for t in range(nHDs) ]   #restart\n",
    "HDvPop = [0 for t in range(nHDs)]\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        HDvPop[t] += unitPop[u]\n",
    "plt.axvline(aDP, ls=\"--\")\n",
    "plt.axvline(0.99*aDP, ls=\"dotted\")\n",
    "plt.axvline(1.01*aDP, ls=\"dotted\")\n",
    "plt.hist([HDvPop[t] for t in popHDlist],bins=20)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "827b8496-d66d-40ae-9780-a20243a54f92",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "here are the HD centers for 155 cantFill HDs with border or big enclaves\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"here are the HD centers for\",len(cantFill),\"cantFill HDs with border or big enclaves\")\n",
    "for u in borderUnits:\n",
    "    plotPoly(unitGeom[u],0.1)\n",
    "for t in cantFill:\n",
    "    plotPoly(HDCP[t].buffer(0.02))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "d4eec53d-e431-4e8d-a430-31ef4d1aa8c7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "working on avg unit-to-HDcp dist for HD 0\n",
      "working on avg unit-to-HDcp dist for HD 800\n",
      "working on avg unit-to-HDcp dist for HD 1602\n",
      "working on avg unit-to-HDcp dist for HD 2402\n",
      "working on avg unit-to-HDcp dist for HD 3203\n",
      "working on avg unit-to-HDcp dist for HD 4004\n",
      "working on avg unit-to-HDcp dist for HD 4806\n",
      "working on avg unit-to-HDcp dist for HD 5606\n",
      "working on avg unit-to-HDcp dist for HD 6406\n",
      "working on avg unit-to-HDcp dist for HD 7206\n",
      "working on avg unit-to-HDcp dist for HD 8006\n",
      "working on avg unit-to-HDcp dist for HD 8807\n",
      "all unit-toHDcp distances computed\n"
     ]
    }
   ],
   "source": [
    "barredJettisonSet = set([]) #for basic muni snap, there are no special corner units to freeze\n",
    "avgDist = [0. for t in range(nHDs)]  #about 6sec per 1000 HDs\n",
    "for i,t in enumerate(popHDlist):\n",
    "    if i%800 == 0:\n",
    "        print(\"working on avg unit-to-HDcp dist for HD\",t)\n",
    "    avgDist[t] =  np.sum([unitPop[u]*unitCP[u].distance(hdCP[t]) for u in HDunitList[t] ]) / HDvPop[t]\n",
    "print(\"all unit-toHDcp distances computed\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "76225203-dcf1-4845-b6a2-3b75e3749b01",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "for this code, we don't have any clusters\n"
     ]
    }
   ],
   "source": [
    "print(\"for this code, we don't have any clusters\")\n",
    "allUnits = [u for u in range(nUnits)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "id": "e9ac0605-49ba-43f3-8063-82f83351d50d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "155\n"
     ]
    }
   ],
   "source": [
    "print(len(cantFill))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "id": "be000bf6-65fd-4774-9f32-c5572416ea3b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "this MUSTFREE code doesn't work right if a set of border units is surrounded by other border units\n",
      "this code will solve large enclaves so HD and complement are contiguous for 155 HDs\n",
      "working on HD 14 cantFill 0 of 155 .Time is now 0\n",
      "giving up for HD 1055 there are only 1 freeing units for 1 enclaves\n",
      "giving up for HD 1095 there are only 1 freeing units for 1 enclaves\n",
      "working on HD 1214 cantFill 20 of 155 .Time is now 0\n",
      "giving up for HD 1522 there are only 1 freeing units for 1 enclaves\n",
      "giving up for HD 1572 there are only 1 freeing units for 1 enclaves\n",
      "working on HD 1999 cantFill 40 of 155 .Time is now 0\n",
      "working on HD 3788 cantFill 60 of 155 .Time is now 0\n",
      "working on HD 4128 cantFill 80 of 155 .Time is now 0\n",
      "working on HD 4287 cantFill 100 of 155 .Time is now 0\n",
      "working on HD 4583 cantFill 120 of 155 .Time is now 1\n",
      "working on HD 6409 cantFill 140 of 155 .Time is now 1\n",
      "after the MustFree code run, we have the following for cluster usage\n",
      "current avg use and its sd are 1.01339 0.1048\n"
     ]
    },
    {
     "data": {
      "image/png": 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1+vRpXXzxxWHttbW1SkxM1OWXX677779fx48f77FGe3u7gsFg2AYAAIYvW4Hl2LFj6uzslMvlCmt3uVzy+/3nVeMXv/iFUlJSwkLPzJkz9eKLL8rn8+mpp57Su+++q1tuuUWdnZ3d1igvL1dcXFxoS0tLs3MYAABgiBk1kD/sySef1ObNm1VbW6vo6OhQ+5w5c0J/vvLKKzVt2jRNnDhRtbW1uvHGG8+qU1JSIq/XG3odDAYJLQAADGO2zrAkJCTI4XAoEAiEtQcCASUlJZ1z39WrV+vJJ5/Um2++qWnTpp2zb0ZGhhISErRnz55u33c6nYqNjQ3bAADA8GUrsERFRSknJydsweyZBbQFBQU97rdy5UotX75cNTU1ys3N/cafc/DgQR0/flzJycl2hgcAAIYp21cJeb1erV+/Xhs3btSuXbt0//33q62tTcXFxZKkoqIilZSUhPo/9dRTWrp0qTZs2KD09HT5/X75/X61trZKklpbW/Xoo4/q/fff1/79++Xz+TRr1ixlZmbK4/H00WECAIChzPYalsLCQh09elSlpaXy+/3Kzs5WTU1NaCFuU1OTIiO/zkHr1q1TR0eHfvjDH4bVKSsr0xNPPCGHw6GPPvpIGzduVHNzs1JSUnTzzTdr+fLlcjqdF3h4AABgOOjVotsFCxZowYIF3b5XW1sb9nr//v3nrBUTE6M33nijN8MAAAAjBM8SAgAAxiOwAAAA4xFYAACA8QgsAADAeAQWAABgPAILAAAwHoEFAAAYj8ACAACMR2ABAADGI7AAAADjEVgAAIDxCCwAAMB4BBYAAGA8AgsAADAegQUAABiPwAIAAIxHYAEAAMYjsAAAAOMRWAAAgPEILAAAwHgEFgAAYDwCCwAAMB6BBQAAGI/AAgAAjEdgAQAAxiOwAAAA4xFYAACA8QgsAADAeAQWAABgPAILAAAwHoEFAAAYj8ACAACMR2ABAADGI7AAAADj9SqwVFZWKj09XdHR0crPz9eOHTt67Lt+/Xpde+21io+PV3x8vNxu91n9LctSaWmpkpOTFRMTI7fbrU8++aQ3QwMAAMOQ7cBSXV0tr9ersrIy7dy5U1lZWfJ4PDpy5Ei3/WtrazV37ly98847qqurU1pamm6++WYdOnQo1GflypV65plnVFVVpe3bt2vMmDHyeDz64osven9kAABg2IiwLMuys0N+fr6uuuoqPfvss5Kkrq4upaWl6Wc/+5kWL178jft3dnYqPj5ezz77rIqKimRZllJSUvTwww/rkUcekSS1tLTI5XLphRde0Jw5c76xZjAYVFxcnFpaWhQbG2vncAAMAYeaT+lEW0ef191zpFULqxv02s+ma2pqXJ/W/p9DLbp97bZ+qQ0MF3Y+v0fZKdzR0aH6+nqVlJSE2iIjI+V2u1VXV3deNT7//HOdPn1aF198sSRp37598vv9crvdoT5xcXHKz89XXV1dt4Glvb1d7e3todfBYNDOYQAYQg41n5L76Xd16nRnv9SPucih+DFR/VIbQN+xFViOHTumzs5OuVyusHaXy6Xdu3efV41f/OIXSklJCQUUv98fqvH3Nc+89/fKy8u1bNkyO0MHMESdaOvQqdOdqijMVmbi2D6vHz8mSqnjY/q8LoC+ZSuwXKgnn3xSmzdvVm1traKjo3tdp6SkRF6vN/Q6GAwqLS2tL4YIwFCZiWP5agUYwWwFloSEBDkcDgUCgbD2QCCgpKSkc+67evVqPfnkk3r77bc1bdq0UPuZ/QKBgJKTk8NqZmdnd1vL6XTK6XTaGToAABjCbF0lFBUVpZycHPl8vlBbV1eXfD6fCgoKetxv5cqVWr58uWpqapSbmxv23oQJE5SUlBRWMxgMavv27eesCQAARg7bXwl5vV7NmzdPubm5ysvLU0VFhdra2lRcXCxJKioqUmpqqsrLyyVJTz31lEpLS7Vp0yalp6eH1qWMHTtWY8eOVUREhBYuXKgVK1Zo0qRJmjBhgpYuXaqUlBTNnj27744UAAAMWbYDS2FhoY4eParS0lL5/X5lZ2erpqYmtGi2qalJkZFfn7hZt26dOjo69MMf/jCsTllZmZ544glJ0qJFi9TW1qb77rtPzc3Nmj59umpqai5onQsAABg+bN+HxUTchwUYvobq/UyG6riBgWTn85tnCQEAAOMRWAAAgPEILAAAwHgEFgAAYDwCCwAAMB6BBQAAGI/AAgAAjEdgAQAAxiOwAAAA4xFYAACA8QgsAADAeAQWAABgPAILAAAwHoEFAAAYj8ACAACMR2ABAADGI7AAAADjEVgAAIDxCCwAAMB4BBYAAGA8AgsAADAegQUAABiPwAIAAIxHYAEAAMYjsAAAAOMRWAAAgPEILAAAwHgEFgAAYDwCCwAAMB6BBQAAGI/AAgAAjEdgAQAAxiOwAAAA4xFYAACA8QgsAADAeL0KLJWVlUpPT1d0dLTy8/O1Y8eOHvv+9a9/1Q9+8AOlp6crIiJCFRUVZ/V54oknFBEREbZNnjy5N0MDAADDkO3AUl1dLa/Xq7KyMu3cuVNZWVnyeDw6cuRIt/0///xzZWRk6Mknn1RSUlKPdb/1rW/ps88+C23btm2zOzQAADBM2Q4sa9as0fz581VcXKwpU6aoqqpKo0eP1oYNG7rtf9VVV2nVqlWaM2eOnE5nj3VHjRqlpKSk0JaQkGB3aAAAYJiyFVg6OjpUX18vt9v9dYHISLndbtXV1V3QQD755BOlpKQoIyNDd911l5qamnrs297ermAwGLYBAIDhy1ZgOXbsmDo7O+VyucLaXS6X/H5/rweRn5+vF154QTU1NVq3bp327duna6+9VidPnuy2f3l5ueLi4kJbWlpar382AAAwnxFXCd1yyy268847NW3aNHk8Hm3dulXNzc3605/+1G3/kpIStbS0hLYDBw4M8IgBAMBAGmWnc0JCghwOhwKBQFh7IBA454Jau8aPH6/LLrtMe/bs6fZ9p9N5zvUwAABgeLF1hiUqKko5OTny+Xyhtq6uLvl8PhUUFPTZoFpbW7V3714lJyf3WU0AADB02TrDIkler1fz5s1Tbm6u8vLyVFFRoba2NhUXF0uSioqKlJqaqvLycklfLdT9+OOPQ38+dOiQGhoaNHbsWGVmZkqSHnnkEd1xxx36p3/6Jx0+fFhlZWVyOByaO3duXx0nAAAYwmwHlsLCQh09elSlpaXy+/3Kzs5WTU1NaCFuU1OTIiO/PnFz+PBhffvb3w69Xr16tVavXq0ZM2aotrZWknTw4EHNnTtXx48f16WXXqrp06fr/fff16WXXnqBhwcAAIYD24FFkhYsWKAFCxZ0+96ZEHJGenq6LMs6Z73Nmzf3ZhgAAGCEMOIqIQAAgHMhsAAAAOMRWAAAgPEILAAAwHgEFgAAYDwCCwAAMB6BBQAAGI/AAgAAjEdgAQAAxiOwAAAA4xFYAACA8QgsAADAeAQWAABgPAILAAAwHoEFAAAYj8ACAACMR2ABAADGI7AAAADjEVgAAIDxCCwAAMB4BBYAAGA8AgsAADAegQUAABiPwAIAAIxHYAEAAMYjsAAAAOMRWAAAgPEILAAAwHgEFgAAYDwCCwAAMB6BBQAAGI/AAgAAjDdqsAcAAMPZniOtfV4zfkyUUsfH9HldwGQEFgDoB/FjohRzkUMLqxv6vHbMRQ69/fAMQgtGlF4FlsrKSq1atUp+v19ZWVlau3at8vLyuu3717/+VaWlpaqvr9ff/vY3/cu//IsWLlx4QTUBwHSp42P09sMzdKKto0/r7jnSqoXVDTrR1kFgwYhiO7BUV1fL6/WqqqpK+fn5qqiokMfjUWNjoxITE8/q//nnnysjI0N33nmnfv7zn/dJTQAYClLHxxAqgD5ie9HtmjVrNH/+fBUXF2vKlCmqqqrS6NGjtWHDhm77X3XVVVq1apXmzJkjp9PZJzUBAMDIYiuwdHR0qL6+Xm63++sCkZFyu92qq6vr1QB6U7O9vV3BYDBsAwAAw5etwHLs2DF1dnbK5XKFtbtcLvn9/l4NoDc1y8vLFRcXF9rS0tJ69bMBAMDQMCTvw1JSUqKWlpbQduDAgcEeEgAA6Ee2Ft0mJCTI4XAoEAiEtQcCASUlJfVqAL2p6XQ6e1wPAwAAhh9bZ1iioqKUk5Mjn88Xauvq6pLP51NBQUGvBtAfNQEAwPBi+7Jmr9erefPmKTc3V3l5eaqoqFBbW5uKi4slSUVFRUpNTVV5ebmkrxbVfvzxx6E/Hzp0SA0NDRo7dqwyMzPPqyYAABjZbAeWwsJCHT16VKWlpfL7/crOzlZNTU1o0WxTU5MiI78+cXP48GF9+9vfDr1evXq1Vq9erRkzZqi2tva8agIAgJGtV3e6XbBggRYsWNDte2dCyBnp6emyLOuCagIYGg41n+qXO7sCAM8SAtAnDjWfkvvpd3XqdGef1465yKH4MVF9XhfA0EFgAdAnTrR16NTpTlUUZiszcWyf1ubpxAAILAD6VGbiWE1NjRvsYQAYZobkjeMAAMDIQmABAADGI7AAAADjEVgAAIDxCCwAAMB4BBYAAGA8AgsAADAegQUAABiPwAIAAIxHYAEAAMYjsAAAAOMRWAAAgPEILAAAwHgEFgAAYDwCCwAAMB6BBQAAGI/AAgAAjEdgAQAAxiOwAAAA4xFYAACA8QgsAADAeAQWAABgPAILAAAwHoEFAAAYj8ACAACMR2ABAADGI7AAAADjEVgAAIDxCCwAAMB4BBYAAGA8AgsAADDeqMEeAADAvj1HWvulbvyYKKWOj+mX2sCF6FVgqays1KpVq+T3+5WVlaW1a9cqLy+vx/6vvPKKli5dqv3792vSpEl66qmndOutt4bev+eee7Rx48awfTwej2pqanozPAAYtuLHRCnmIocWVjf0S/2Yixx6++EZhBYYx3Zgqa6ultfrVVVVlfLz81VRUSGPx6PGxkYlJiae1f+9997T3LlzVV5erttvv12bNm3S7NmztXPnTk2dOjXUb+bMmXr++edDr51OZy8PCQCGr9TxMXr74Rk60dbR57X3HGnVwuoGnWjr6PPAcqj5VL+MWeKs0EhhO7CsWbNG8+fPV3FxsSSpqqpKr7/+ujZs2KDFixef1f83v/mNZs6cqUcffVSStHz5cr311lt69tlnVVVVFerndDqVlJTU2+MAgBEjdXzMkPqAPtR8Su6n39Wp0539Up+zQiODrcDS0dGh+vp6lZSUhNoiIyPldrtVV1fX7T51dXXyer1hbR6PR1u2bAlrq62tVWJiouLj43XDDTdoxYoVuuSSS7qt2d7ervb29tDrYDBo5zAAAAPoRFuHTp3uVEVhtjITx/Zp7f48KwSz2Aosx44dU2dnp1wuV1i7y+XS7t27u93H7/d329/v94dez5w5U9///vc1YcIE7d27V4899phuueUW1dXVyeFwnFWzvLxcy5YtszN0AMAgy0wcq6mpcYM9DAxRRlwlNGfOnNCfr7zySk2bNk0TJ05UbW2tbrzxxrP6l5SUhJ21CQaDSktLG5CxAgCAgWfrPiwJCQlyOBwKBAJh7YFAoMf1J0lJSbb6S1JGRoYSEhK0Z8+ebt93Op2KjY0N2wAAwPBlK7BERUUpJydHPp8v1NbV1SWfz6eCgoJu9ykoKAjrL0lvvfVWj/0l6eDBgzp+/LiSk5PtDA8AAAxTtu906/V6tX79em3cuFG7du3S/fffr7a2ttBVQ0VFRWGLch966CHV1NTo6aef1u7du/XEE0/ogw8+0IIFCyRJra2tevTRR/X+++9r//798vl8mjVrljIzM+XxeProMAEAwFBmew1LYWGhjh49qtLSUvn9fmVnZ6umpia0sLapqUmRkV/noKuvvlqbNm3SkiVL9Nhjj2nSpEnasmVL6B4sDodDH330kTZu3Kjm5malpKTo5ptv1vLly7kXCwAAkNTLRbcLFiwInSH5e7W1tWe13Xnnnbrzzju77R8TE6M33nijN8MAAAAjBA8/BAAAxiOwAAAA4xlxHxYAA6e/nunSX08PBgCJwAKMKAPxTJf4MVH9UhvAyEZgAUaQ/nymi8RTcwH0HwILMALxTBcAQw2LbgEAgPEILAAAwHgEFgAAYDwCCwAAMB6BBQAAGI/AAgAAjEdgAQAAxiOwAAAA4xFYAACA8QgsAADAeAQWAABgPAILAAAwHg8/BAx1qPmUTrR19GnNPUda+7QeAAwUAgtgoEPNp+R++l2dOt3Z57VjLnIofkxUn9cFgP5EYAEMdKKtQ6dOd6qiMFuZiWP7tHb8mCiljo/p05oA0N8ILIDBMhPHampq3GAPAyNMX391yFeR6AsEFgCApK/OvsVc5NDC6oY+r81XkbhQBBYAgCQpdXyM3n54Rp8v9pb4KhIXjsACAAhJHR9DsICRuA8LAAAwHoEFAAAYj8ACAACMxxoWAMCQ1x+XTrNQ2CwEFgDAkNXfl2JX3Z2jS/rhcmzCkH0EFgDAkNVfl2Ifb+vQT1+q17wNO/q07hkxFzn09sMzCC02EFgAAENaf12K3V/3pNlzpFULqxt0oq2DwGIDgQW4AP3xRGWJW5kDJuCeNGYhsAC91J9PVJa4lTkA/L96FVgqKyu1atUq+f1+ZWVlae3atcrLy+ux/yuvvKKlS5dq//79mjRpkp566indeuutofcty1JZWZnWr1+v5uZmXXPNNVq3bp0mTZrUm+EBA6I/n6gssSgPgH39ddZXGvzfSbYDS3V1tbxer6qqqpSfn6+Kigp5PB41NjYqMTHxrP7vvfee5s6dq/Lyct1+++3atGmTZs+erZ07d2rq1KmSpJUrV+qZZ57Rxo0bNWHCBC1dulQej0cff/yxoqOjL/wogX7EE5UBmGAgzvoO5kJh24FlzZo1mj9/voqLiyVJVVVVev3117VhwwYtXrz4rP6/+c1vNHPmTD366KOSpOXLl+utt97Ss88+q6qqKlmWpYqKCi1ZskSzZs2SJL344otyuVzasmWL5syZcyHHBwCAkfp6rdqeI639dtbXhIXCtgJLR0eH6uvrVVJSEmqLjIyU2+1WXV1dt/vU1dXJ6/WGtXk8Hm3ZskWStG/fPvn9frnd7tD7cXFxys/PV11dXbeBpb29Xe3t7aHXLS0tkqRgMGjncM7b0eAXOtra/s0dMaJ8erRNXe2fq/VkUMFgxGAPB8AQMarzC0V1faH/78X3+rx29EWRmnzJKKWM69vfSa0nu/rl992Zz23Lsr6xr63AcuzYMXV2dsrlcoW1u1wu7d69u9t9/H5/t/39fn/o/TNtPfX5e+Xl5Vq2bNlZ7Wlpaed3IEAfKqgY7BEAwNeuWNV/tfvr993JkycVF3fur9aH5FVCJSUlYWdturq69H//93+65JJLFBExOP+nGwwGlZaWpgMHDig2NnZQxjDUMYcXjjm8cMzhhWMO+8ZImEfLsnTy5EmlpKR8Y19bgSUhIUEOh0OBQCCsPRAIKCkpqdt9kpKSztn/zH8DgYCSk5PD+mRnZ3db0+l0yul0hrWNHz/ezqH0m9jY2GH7F2ugMIcXjjm8cMzhhWMO+8Zwn8dvOrNyhq2nNUdFRSknJ0c+ny/U1tXVJZ/Pp4KCgm73KSgoCOsvSW+99Vao/4QJE5SUlBTWJxgMavv27T3WBAAAI4vtr4S8Xq/mzZun3Nxc5eXlqaKiQm1tbaGrhoqKipSamqry8nJJ0kMPPaQZM2bo6aef1m233abNmzfrgw8+0O9+9ztJUkREhBYuXKgVK1Zo0qRJocuaU1JSNHv27L47UgAAMGTZDiyFhYU6evSoSktL5ff7lZ2drZqamtCi2aamJkVGfn3i5uqrr9amTZu0ZMkSPfbYY5o0aZK2bNkSugeLJC1atEhtbW2677771NzcrOnTp6umpmZI3YPF6XSqrKzsrK+qcP6YwwvHHF445vDCMYd9g3kMF2Gdz7VEAAAAg8jWGhYAAIDBQGABAADGI7AAAADjEVgAAIDxCCw2VFZWKj09XdHR0crPz9eOHTvOa7/NmzcrIiKCy7Rlfw6bm5v14IMPKjk5WU6nU5dddpm2bt06QKM1k905rKio0OWXX66YmBilpaXp5z//ub744osBGq15/vznP+uOO+5QSkqKIiIiQs81O5fa2lr98z//s5xOpzIzM/XCCy/0+zhNZncOX331Vd1000269NJLFRsbq4KCAr3xxhsDM1hD9ebv4Rn/9V//pVGjRvV4c9XhisBynqqrq+X1elVWVqadO3cqKytLHo9HR44cOed++/fv1yOPPKJrr712gEZqLrtz2NHRoZtuukn79+/Xv/7rv6qxsVHr169XamrqAI/cHHbncNOmTVq8eLHKysq0a9cuPffcc6qurtZjjz02wCM3R1tbm7KyslRZWXle/fft26fbbrtN119/vRoaGrRw4ULde++9I/oD1+4c/vnPf9ZNN92krVu3qr6+Xtdff73uuOMOffjhh/08UnPZncMzmpubVVRUpBtvvLGfRmYwC+clLy/PevDBB0OvOzs7rZSUFKu8vLzHfb788kvr6quvtn7/+99b8+bNs2bNmjUAIzWX3Tlct26dlZGRYXV0dAzUEI1ndw4ffPBB64Ybbghr83q91jXXXNOv4xwqJFn/9m//ds4+ixYtsr71rW+FtRUWFloej6cfRzZ0nM8cdmfKlCnWsmXL+n5AQ5CdOSwsLLSWLFlilZWVWVlZWf06LtNwhuU8dHR0qL6+Xm63O9QWGRkpt9uturq6Hvf75S9/qcTERP3kJz8ZiGEarTdz+O///u8qKCjQgw8+KJfLpalTp+rXv/61Ojs7B2rYRunNHF599dWqr68PfW306aefauvWrbr11lsHZMzDQV1dXdicS5LH4znnv32cW1dXl06ePKmLL754sIcypDz//PP69NNPVVZWNthDGRRD8mnNA+3YsWPq7OwM3c33DJfLpd27d3e7z7Zt2/Tcc8+poaFhAEZovt7M4aeffqr/+I//0F133aWtW7dqz549euCBB3T69OkR+Q+2N3P44x//WMeOHdP06dNlWZa+/PJL/fSnPx3RXwnZ5ff7u53zYDCoU6dOKSYmZpBGNnStXr1ara2t+tGPfjTYQxkyPvnkEy1evFj/+Z//qVGjRuZHN2dY+sHJkyd19913a/369UpISBjs4QxZXV1dSkxM1O9+9zvl5OSosLBQjz/+uKqqqgZ7aENGbW2tfv3rX+u3v/2tdu7cqVdffVWvv/66li9fPthDwwi1adMmLVu2TH/605+UmJg42MMZEjo7O/XjH/9Yy5Yt02WXXTbYwxk0IzOm2ZSQkCCHw6FAIBDWHggElJSUdFb/vXv3av/+/brjjjtCbV1dXZKkUaNGqbGxURMnTuzfQRvG7hxKUnJysi666CI5HI5Q2xVXXCG/36+Ojg5FRUX165hN05s5XLp0qe6++27de++9kqQrr7wy9Nyuxx9/POy5X+heUlJSt3MeGxvL2RWbNm/erHvvvVevvPLKWV+zoWcnT57UBx98oA8//FALFiyQ9NVnimVZGjVqlN58803dcMMNgzzK/sdvq/MQFRWlnJwc+Xy+UFtXV5d8Pp8KCgrO6j958mT95S9/UUNDQ2j77ne/G7rKIC0tbSCHbwS7cyhJ11xzjfbs2RMKe5L0v//7v0pOTh5xYUXq3Rx+/vnnZ4WSMwHQ4jFi56WgoCBsziXprbfe6nHO0b2XX35ZxcXFevnll3XbbbcN9nCGlNjY2LM+U37605/q8ssvV0NDg/Lz8wd7iANjkBf9DhmbN2+2nE6n9cILL1gff/yxdd9991njx4+3/H6/ZVmWdffdd1uLFy/ucX+uErI/h01NTda4ceOsBQsWWI2NjdZrr71mJSYmWitWrBisQxh0duewrKzMGjdunPXyyy9bn376qfXmm29aEydOtH70ox8N1iEMupMnT1offvih9eGHH1qSrDVr1lgffvih9be//c2yLMtavHixdffdd4f6f/rpp9bo0aOtRx991Nq1a5dVWVlpORwOq6amZrAOYdDZncM//vGP1qhRo6zKykrrs88+C23Nzc2DdQiDzu4c/r2ReJUQgcWGtWvXWv/4j/9oRUVFWXl5edb7778fem/GjBnWvHnzetyXwPIVu3P43nvvWfn5+ZbT6bQyMjKsX/3qV9aXX345wKM2i505PH36tPXEE09YEydOtKKjo620tDTrgQcesE6cODHwAzfEO++8Y0k6azszb/PmzbNmzJhx1j7Z2dlWVFSUlZGRYT3//PMDPm6T2J3DGTNmnLP/SNSbv4f/r5EYWCIsi/PCAADAbKxhAQAAxiOwAAAA4xFYAACA8QgsAADAeAQWAABgPAILAAAwHoEFAAAYj8ACAACMR2ABAADGI7AAAADjEVgAAIDxCCwAAMB4/z//s+H2Jk6EyQAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"this MUSTFREE code doesn't work right if a set of border units is surrounded by other border units\")\n",
    "#THIS IS THE MUSTFREE CODE - for high-pop HDs with map-border enclaves, can't fill; \n",
    "#  must jettison some inHD map-boundary units to connect the enclave to the larger complement\n",
    "#For each HD to be triaged, define the list(s) of contiguous enclave units that are on the map boundary, \n",
    "#  and the in-HD map-boundary segments.  ID which in-HD MBS's adjoin one vs. two enclaves.\n",
    "#     Fill all internal enclaves, and all boundary enclaves < 0.05 aDP.\n",
    "#   Then each loop, look for boundary enclaves that can be filled without overpopping.\n",
    "#     If none, pick the 1/2 has-1-boundary-enclave-neighbor that is least painful to jettison to free an enclave.\n",
    "#       (Jettison score based on pop-to-Free and distance from HDcP)\n",
    "#         Update HDpop, HDlist, and enclave & HD-boundary associations, then re-loop\n",
    "# Later, we will swell-fill to square up pop (w/ checkEnclave) biasing toward close-to-hdCP, underused\n",
    "borderSet = set(borderUnits)\n",
    "debug, debugPlot = False, False\n",
    "startTime = time.time()  #takes about 1.5sec per HD triage\n",
    "clusterJettisonBoost = 3.  #this discourages jettisoning of underused clusters\n",
    "print(\"this code will solve large enclaves so HD and complement are contiguous for\",len(cantFill),\"HDs\")\n",
    "nEnclavesPerHD = [0 for t in range(nHDs)]\n",
    "HDenclaveLists = [list() for t in range(nHDs)]\n",
    "stillCantFill = list()  #those we can't fill due to border topology problem\n",
    "for iii,t in enumerate(cantFill):\n",
    "    if iii %20 == 0:\n",
    "        print(\"working on HD\",t,\"cantFill\",iii,\"of\",len(cantFill),\".Time is now\",int(time.time() - startTime) )\n",
    "    shedUs = list()    \n",
    "    enclaveLists = getEnclaveLists(HDunitList[t], unitNbrs)\n",
    "    nEnclavesPerHD[t] = len(enclaveLists)\n",
    "    HDenclaveLists[t] = enclaveLists.copy()\n",
    "    if debug:\n",
    "        print(\"pre-adjust HDpop for HD\",t,\"is\",HDvPop[t],\"I found\",len(enclaveLists),\"TOTAL enclaves\")\n",
    "    internalEnclaves, edgeEnclaves, combinedEnclBorderList = list(), list(), list()\n",
    "    for jjj, eL in enumerate(enclaveLists.copy() ):\n",
    "        enclaveBorderList = list ( set(eL).intersection(borderSet) )\n",
    "        if debug:\n",
    "            print(\"In enclave\",jjj,\"I found\",len(enclaveBorderList),\"units that were enclaved and are in the map borderSet\")\n",
    "        combinedEnclBorderList += enclaveBorderList\n",
    "        ePop = np.sum( [unitPop[u] for u in eL] )\n",
    "        if len(enclaveBorderList) == 0 or ePop < 0.05 * aDP:  #internal or small enclave.  Fill it\n",
    "            if ePop > 0:  #in a prev treatment, could be an empty (surrounded) unit that we don't care about\n",
    "                HDunitList[t] += eL\n",
    "                HDvPop[t] += ePop\n",
    "            internalEnclaves.append(eL)\n",
    "        else:\n",
    "            edgeEnclaves.append(eL)\n",
    "    if debug:\n",
    "        print(\"Of these\",len(internalEnclaves),\"were internal or small, so I filled them, leaving\",\n",
    "              len(edgeEnclaves),\"non-small border = edge enclaves\" )\n",
    "    if debugPlot:\n",
    "        print(\"Here is the original HD, internal enclaves ('x') and non-small border enclaves by enclave no\")\n",
    "        plotPoly(hdCP[t].buffer(0.3))\n",
    "        for u in HDunitList[t]:\n",
    "            if unitPop[u] > 0:\n",
    "                plotPoly(unitGeom[u],0.2)\n",
    "        for L in internalEnclaves:\n",
    "            for u in L:\n",
    "                if unitPop[u] > 0:\n",
    "                    plotPoly(unitGeom[u],1.5)\n",
    "                    plotCenter(\"x\",unitCP[u],8)\n",
    "        for L in edgeEnclaves: #############\n",
    "            for u in L:\n",
    "                if unitPop[u] > 0:\n",
    "                    plotPoly(unitGeom[u])\n",
    "                    #plotCenter(\"e\",unitCP[u],8)\n",
    "        #plotPoly(MAP,0.4)\n",
    "        #plt.show()\n",
    "    enclaveLists, combinedEnclBorderSet = list(), set(combinedEnclBorderList)\n",
    "    if len(edgeEnclaves) > 0:\n",
    "        # Now, we order by chain connectivity of HD and enclave sublists to be H0-E0-H1-E1 ... En-Hn+1\n",
    "        nonHDborderSet = borderSet.difference(  set(HDunitList[t]) )\n",
    "        nonHDlongBorderSet = nonHDborderSet.difference(combinedEnclBorderSet) #long=non HD boundary excluding enclaves\n",
    "        remainingEnclBorderSet = combinedEnclBorderSet.copy()\n",
    "        remainingHDborderSet =   borderSet.intersection(set(HDunitList[t]) )\n",
    "        #Now find the \"HDender\" unit which borders the non-enclave nonHD boundary, then find opp end of this HD bdry piece\n",
    "        HDender = list(set(getAdjoiners(nonHDlongBorderSet,unitNbrs)).intersection(remainingHDborderSet) )[0]\n",
    "        firstHDborderSet = getContigFromStarter(HDender,remainingHDborderSet,unitNbrs)\n",
    "        HDstarter = list(set(getAdjoiners(remainingEnclBorderSet,unitNbrs)).intersection(firstHDborderSet))[0]\n",
    "        HDborderSublists = [ list(firstHDborderSet) ]\n",
    "        unused = [1 for eL in edgeEnclaves]\n",
    "        eLadjoiners = [getAdjoiners(eL,unitNbrs) for eL in edgeEnclaves ]\n",
    "        for j in range(len(edgeEnclaves)): #find the enclave with the most HDstarter neighbors (at least 1)\n",
    "            found = False\n",
    "            for i,eL in enumerate(edgeEnclaves):\n",
    "                if unused[i] == 1:\n",
    "                    HDadjSet = set(HDborderSublists[j]).intersection(set(eLadjoiners[i]))\n",
    "                    if len(HDadjSet) > 0:\n",
    "                        unused[i] = 0\n",
    "                        eNo = i\n",
    "                        found = True\n",
    "                        remainingEnclBorderSet = remainingEnclBorderSet.difference(set(edgeEnclaves[eNo]) )\n",
    "                        enclaveLists.append(edgeEnclaves[eNo])\n",
    "                        remainingHDborderSet = remainingHDborderSet.difference(set(HDborderSublists[j]) )\n",
    "                        if len(remainingHDborderSet) > 0: #for narrow peninsulas, separated border units may connect\n",
    "                            #this if statement was added for legisl OH\n",
    "                            HDstarter = list(set(eLadjoiners[i]).intersection(remainingHDborderSet))[0]       \n",
    "                            HDborderSublists.append(getContigFromStarter(HDstarter,remainingHDborderSet,unitNbrs) )\n",
    "                        break\n",
    "                if found:\n",
    "                    break\n",
    "\n",
    "        enclavePops = [np.sum([unitPop[u] for u in L]) for L in enclaveLists]\n",
    "        #print(\"prior to adjustments, border enclavePops are\",enclavePops)         \n",
    "\n",
    "        nHDBS, nEnclaves = len(HDborderSublists), len(enclaveLists)\n",
    "        popToFree, freeingCounties, freeingUnits = [0. for n in range(nHDBS)], [list() for n in range(nHDBS) \n",
    "                                                                               ],[list() for n in range(nHDBS)]\n",
    "        for j,L in enumerate(HDborderSublists):\n",
    "            for u in L:\n",
    "                if int(allUnits[u]) == allUnits[u]:  #this border unit is a standard unit ##vtd in vanilla code\n",
    "                    c = countyNo[u] #countyNo[parentVTDno[allUnits[u]]]   #countyNo[allUnits[u]]\n",
    "                    if c not in freeingCounties[j]:\n",
    "                        if \"weDistinguishTinyCounties\" == \"yup\": #countyPop[c] < 0.1 * aDP: ##plan to add all in-county pop\n",
    "                            freeingCounties[j].append(c)\n",
    "                        else:\n",
    "                            popToFree[j] += unitPop[u]\n",
    "                            freeingUnits[j].append(u)\n",
    "                else: #border unit is a full county or cluster, or in a dense county.  Add the whole unit pop\n",
    "                    popToFree[j] += unitPop[u]\n",
    "                    freeingUnits[j].append(u)\n",
    "            for c in freeingCounties[j]:  #include ALL in-HD pop from each non-unit border county, not just its border units\n",
    "                #plotPoly(countyGeom[c],0.1)\n",
    "                for u in countyUnitList[c]:\n",
    "                    if u in HDunitList[t]:\n",
    "                        popToFree[j] += unitPop[u]\n",
    "                        freeingUnits[j].append(u)\n",
    "        freeingCP = [ getHDcp(  unitCP, unitPop, L) for L in freeingUnits ]\n",
    "        freeingScore = [ pTF/aDP - 0.5*freeingCP[j].distance(hdCP[t]) / avgDist[t] for j,pTF in enumerate(popToFree) ]\n",
    "        for j, fU in enumerate(freeingUnits):  #in above 0.5 is a fudgy\n",
    "            if len(barredJettisonSet.intersection(set(fU)) ) > 0: #has a cluster we want to hold onto\n",
    "                freeingScore[j] += clusterJettisonBoost #  ..so increase its score (make it harder to drop)\n",
    "        if debugPlot:\n",
    "            print(\"plotting the freeing units with negative numbers for each freeing group\")\n",
    "            for j,L in enumerate(freeingUnits):\n",
    "                for u in L:\n",
    "                    if unitPop[u] > 0:\n",
    "                        #plotPoly(unitGeom[u],0.5)\n",
    "                        plotCenter(\"-\"+str(j),unitGeom[u],6)\n",
    "                        pass\n",
    "            print(\"plotting the enclaveLists, with + numbers for each enclave\")\n",
    "            for j,L in enumerate(enclaveLists):\n",
    "                for u in L:\n",
    "                    if unitPop[u] > 0:\n",
    "                        plotPoly(unitGeom[u])\n",
    "                        plotCenter(j,unitCP[u],8)\n",
    "                        pass\n",
    "    \n",
    "    while len(enclaveLists) > 0:\n",
    "        if len(freeingUnits) <= len(enclaveLists):  #this is new for COI615 Congr\n",
    "            print(\"giving up for HD\",t,\"there are only\",len(freeingUnits),\"freeing units for\",len(enclaveLists),\"enclaves\")\n",
    "            stillCantFill.append(t)\n",
    "            break\n",
    "        if HDvPop[t] + np.min(enclavePops) < 1.05*aDP or np.min(enclavePops) < 0.05 * aDP:  #fill the smallest enclave\n",
    "            eNo = enclavePops.index(np.min(enclavePops))\n",
    "            HDunitList[t] += enclaveLists[eNo]\n",
    "            HDvPop[t] += enclavePops[eNo]\n",
    "            #print(t,\"=t. Absorbing enclave\",eNo,\"with pop\",enclavePops[eNo],\"HD total pop now\",int(HDfreePop[t]) )\n",
    "            enclaveBUs = list(set(enclaveLists[eNo]).intersection(set(borderUnits)) )\n",
    "            enclaveBpop = np.sum([unitPop[u] for u in enclaveBUs])\n",
    "            sNo, dropped_sNo = eNo, eNo+1\n",
    "            freeingScore[sNo] += freeingScore[sNo+1]+enclaveBpop/aDP\n",
    "            freeingUnits[sNo] += freeingUnits[sNo+1]+enclaveBUs\n",
    "            popToFree[sNo]    +=    popToFree[sNo+1]+enclaveBpop\n",
    "        else: #jettison one of the two end HD border lists; pick the less painful path to freedom\n",
    "            #distList = [hdCP[t].distance(unitCP[u]) for u in HDunitList[t] ]     #update from vanilla HD\n",
    "            starterU = homeU[t] #HDunitList[t][distList.index(np.min(distList))]  #update from vanilla HD\n",
    "            eNo, dropped_sNo = 0,0\n",
    "            if starterU not in freeingUnits[-1]:  #we can't drop the home unit, even to save an underused corner\n",
    "                if freeingScore[-1] < freeingScore[0] or starterU in freeingUnits[0]:\n",
    "                    eNo, dropped_sNo = len(enclaveLists)-1,len(enclaveLists)\n",
    "            barredIncluded0 = barredJettisonSet.intersection(set(freeingUnits[0]))\n",
    "            barredIncluded_1 = barredJettisonSet.intersection(set(freeingUnits[-1]))\n",
    "            #if len(barredIncluded0.union(barredIncluded_1)) > 0:\n",
    "            #    print(\"We are considering dropping an end unit to free from t\",t,\". Chosen, beg, end, scores are\")\n",
    "            #    print(dropped_sNo,barredIncluded0, barredIncluded_1, freeingScore[0], freeingScore[-1])\n",
    "            if homeU[t] in freeingUnits[dropped_sNo]:\n",
    "                print(\"WARNING, about to drop unit\",homeU[t],\"from HD\",t,\"; its dropped_sNo is\",dropped_sNo)\n",
    "                print(\"  Is the homeU in the final set of freeing units?\",(homeU[t] in freeingUnits[-1]) )\n",
    "                print(\" len of enclave lists and freeing units (prior to drop) is\",len(enclaveLists),len(freeingUnits) )\n",
    "            HDunitList[t] = list( set(HDunitList[t]).difference(set(freeingUnits[dropped_sNo]) ) )\n",
    "            HDvPop[t] -= popToFree[dropped_sNo]\n",
    "            #print(t,\"= t. Jettisoning HDborder\",dropped_sNo,\"with popToFree\",popToFree[dropped_sNo] )\n",
    "        del enclaveLists[eNo]\n",
    "        del enclavePops[eNo]\n",
    "        if debug:\n",
    "            print(t,\"= t. Now we have\",len(enclaveLists),\"left trapped.  Picked eNo, freeScores were\", eNo,freeingScore)\n",
    "        del freeingScore[dropped_sNo]\n",
    "        del freeingUnits[dropped_sNo]\n",
    "        del popToFree   [dropped_sNo] \n",
    "\n",
    "    #plotPoly(MAP,0.4)\n",
    "    if debugPlot:\n",
    "        plt.show()    \n",
    "        \n",
    "unitUse = [0.]*nUnits\n",
    "lostHomeUnit = list()\n",
    "HDvPop = [np.sum([unitPop[u] for u in HDunitList[t] ]) for t in range(nHDs) ]\n",
    "for t in popHDlist:\n",
    "    if homeU[t] not in HDunitList[t]:\n",
    "        lostHomeUnit.append(t)\n",
    "        revPop = r3((HDvPop[t] + unitPop[homeU[t]])/aDP)\n",
    "        print(\"WARNING - we lost home unit\",homeU[t],\"from HD\",t,\"actual, plus pop/aDP =\",r3(HDvPop[t]/aDP),revPop)\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += HDweight[t]*nDistricts\n",
    "print(\"after the MustFree code run, we have the following for cluster usage\")\n",
    "activeUnitDistro, activeUnitWeights = list(), list()\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] > 0.1:\n",
    "        activeUnitDistro.append(unitUse[u])\n",
    "        activeUnitWeights.append(unitPop[u]/statePop)\n",
    "plt.hist(activeUnitDistro, weights=activeUnitWeights, bins = 20, histtype = \"step\")\n",
    "#plt.show()\n",
    "currAvg, currSD = getWeightedAvgAndSD(activeUnitDistro, activeUnitWeights)\n",
    "print(\"current avg use and its sd are\",r5(currAvg),r5(currSD) )\n",
    "for u, unitNo in enumerate(allUnits):\n",
    "    if unitNo % 1 == 0.25:\n",
    "        print(\"CCB cluster\",int(unitNo),\"= unit\",u,\"with pop\",unitPop[u],\"now has use of\",unitUse[u])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "id": "b039c1ff-3c6a-404c-99a9-e160d53315d7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "classify these unit HDs by contiguity\n",
      "quick classification: who has contiguity problems?\n",
      "working on HD 0 time is now 0\n",
      "working on HD 700 time is now 4\n",
      "working on HD 1402 time is now 7\n",
      "working on HD 2102 time is now 11\n",
      "working on HD 2802 time is now 16\n",
      "working on HD 3503 time is now 19\n",
      "working on HD 4204 time is now 22\n",
      "working on HD 4906 time is now 25\n",
      "working on HD 5606 time is now 29\n",
      "working on HD 6306 time is now 34\n",
      "working on HD 7006 time is now 38\n",
      "working on HD 7706 time is now 40\n",
      "working on HD 8407 time is now 46\n",
      "out of 8934 total HDs, there were 8916.0 contiguous and 8930.0 complement-contiguous HDs\n",
      "0 HDs had both discontiguity problems, while enclave-only = 4 and discontig only= 18\n",
      "stillCantFill enclave only, double, discontigonly 4 0 0\n"
     ]
    }
   ],
   "source": [
    "print(\"classify these unit HDs by contiguity\") #take from vanillaHD\n",
    "\n",
    "### THIS IS THE \"FIND DISCO\" CODE\n",
    "print(\"quick classification: who has contiguity problems?\")\n",
    "nUnbroken, nNoEnclave, smallPieceLists, enclaveLists, sPgenerator, eLgenerator = 0., 0., list(), list(), list(), list()\n",
    "smallPieceLengths, enclaveLengths = list(), list()\n",
    "doubleTroubleList = list()\n",
    "startTime = time.time()\n",
    "for i,t in enumerate(popHDlist):\n",
    "    if i%700 == 0:\n",
    "        print(\"working on HD\",t,\"time is now\",int(time.time() - startTime) )\n",
    "    unbroken, noEnclave,smallPieceList,enclaveList = enclaveCheck(HDunitList[t], unitNbrs,4) #,6) #6 is high (slow) to try to avoid false enclaves\n",
    "    if unbroken:\n",
    "        nUnbroken +=1\n",
    "    if noEnclave:\n",
    "        nNoEnclave +=1\n",
    "    if not unbroken:\n",
    "        smallPieceLists.append(smallPieceList)\n",
    "        smallPieceLengths.append(len(smallPieceList))\n",
    "        sPgenerator.append(t)\n",
    "    if not noEnclave and unbroken:   #district is contiguous but contains 1+ enclave\n",
    "        enclaveLists.append(enclaveList)\n",
    "        enclaveLengths.append(len(enclaveList))\n",
    "        eLgenerator.append(t)\n",
    "    if not noEnclave and not unbroken:  #extremely discontig (\"broken\") HDs can appear to have enclaves;\n",
    "        doubleTroubleList.append(t)\n",
    "print(\"out of\",len(popHDlist),\"total HDs, there were\",nUnbroken,\"contiguous and\",nNoEnclave,\"complement-contiguous HDs\")\n",
    "print(len(doubleTroubleList),\"HDs had both discontiguity problems, while enclave-only =\",len(eLgenerator),\n",
    "      \"and discontig only=\",len(sPgenerator)-len(doubleTroubleList) )\n",
    "for t in lostHomeUnit:\n",
    "    if t in eLgenerator:\n",
    "        print(\"lost-home unit HD\",t,\"is enclave-only\")\n",
    "    if t in doubleTroubleList:\n",
    "        print(\"lost-home unit HD\",t,\"is double-trouble\")\n",
    "    if t in sPgenerator:\n",
    "        print(\"lost-home unit HD\",t,\"is discontig-only\")\n",
    "\n",
    "#did I remove a block which defined stillCantFill ??\n",
    "stillCantFilleLgenerator = set(stillCantFill).intersection(set(eLgenerator))\n",
    "stillCantFilldoubleTroubleList = set(stillCantFill).intersection(set(doubleTroubleList))\n",
    "stillCantFillsPgenerator = set(stillCantFill).intersection(set(sPgenerator))\n",
    "print(\"stillCantFill enclave only, double, discontigonly\",len(stillCantFilleLgenerator),\n",
    "      len(stillCantFilldoubleTroubleList),len(stillCantFillsPgenerator) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "id": "d5ff711c-4bf6-437e-89fe-f30dda1a51a6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "let's visualize over-used and underused units, < 0.75 or > 1.25\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "and here is the histogram of HD pops\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "minUnitUse, maxUnitUse = 0.75, 1.25\n",
    "print(\"let's visualize over-used and underused units, <\",minUnitUse,\"or >\",maxUnitUse)\n",
    "unitUse = [0. for u in range(nUnits)]\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += HDweight[t] * nDistricts\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] < minUnitUse:\n",
    "        plotPoly(unitGeom[u],0.4)\n",
    "        plotCenter(\"u\",unitCP[u])\n",
    "    if unitUse[u] > maxUnitUse:\n",
    "        plotPoly(unitGeom[u], 1.5)\n",
    "for c in range(nCounties):\n",
    "    plotPoly(countyGeom[c],0.1)\n",
    "plt.show()\n",
    "print(\"and here is the histogram of HD pops\")\n",
    "plt.hist([HDvPop[t] for t in popHDlist],bins = [0, 0.6*aDP, 0.7*aDP, 0.85*aDP, 0.9*aDP, 0.95*aDP,\n",
    "         0.98*aDP, aDP, 1.02*aDP, 1.05*aDP, 1.1*aDP, 1.15*aDP, 1.3*aDP, 1.5*aDP, 2.0*aDP])\n",
    "plt.axvline(aDP,ls=\"--\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "id": "c2428bb3-f225-4e1f-aacb-abba4cc2cffb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "before patching, make another copy of the current HD lists\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "pre-patch avg use and its sd are 1.01339 0.1048\n"
     ]
    }
   ],
   "source": [
    "print(\"before patching, make another copy of the current HD lists\")\n",
    "latestHDlist = [HDunitList[t].copy() for t in range(nHDs)]   #More safekeeping\n",
    "latestHDpop, latestUnitUse = [0. for t in range(nHDs)], [0. for u in range(nUnits)]\n",
    "for t in popHDlist:\n",
    "    for u in latestHDlist[t]:\n",
    "        latestHDpop[t] += unitPop[u]\n",
    "        latestUnitUse[u] += nDistricts * HDweight[t]\n",
    "latestUnitWeights, latestUnitDistro = list(), list()\n",
    "for u in range(nUnits):\n",
    "    if latestUnitUse[u] > 0.1:\n",
    "        latestUnitDistro.append(latestUnitUse[u])\n",
    "        latestUnitWeights.append(unitPop[u]/statePop)\n",
    "plt.hist(latestUnitDistro, weights=latestUnitWeights, bins = 20, histtype = \"step\")\n",
    "plt.show()\n",
    "latestAvg, latestSD = getWeightedAvgAndSD(latestUnitDistro, latestUnitWeights)\n",
    "print(\"pre-patch avg use and its sd are\",r5(latestAvg),r5(latestSD) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "id": "09019bdd-53b7-418d-a65a-c46da2358f80",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "we have a total of 22 HDs that have stubborn discontinuities\n"
     ]
    }
   ],
   "source": [
    "#badDiscoList = sPgenerator.copy()  #prep for below\n",
    "badDiscoList = eLgenerator + list(set(sPgenerator).difference(set(doubleTroubleList)))\n",
    "print(\"we have a total of\",len(badDiscoList),\"HDs that have stubborn discontinuities\")\n",
    "CCBgeom = list()  #no CCBgeoms in this ipynb\n",
    "#HDpoly = HDvtdGeom.copy()  #as shortcut, did not generate these shapes for the COI conversion code\n",
    "HDarea = [np.sum([vtdArea[v] for v in HDvtdList[t] ]) for t in range(nHDs) ]\n",
    "HDcircle = [HDCP[t].buffer(0.23456*HDarea[t]**0.5) for t in range(nHDs) ] #approximation\n",
    "HDdiam = [HDarea[h] for h in range(nHDs)]\n",
    "maxGap = maxGap = 0.9 * np.median(unitPop) # = 0.05 * aDP\n",
    "HDnAddedUnits = [list() for h in range(nHDs)]"
   ]
  },
  {
   "cell_type": "raw",
   "id": "7324851c-c09b-4c7b-b281-d7afbd3fe478",
   "metadata": {},
   "source": [
    "HDunitList = [latestHDlist[t].copy() for t in range(nHDs) ] #RESTART\n",
    "HDvPop =     [latestHDpop[t].copy()  for t in range(nHDs) ]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "id": "35510fd8-cf15-403b-8e12-ccca4d3ad405",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "And now, the major disco'd HDs (< 0.75 aDP in HDcP-contig portion and/or enclaves).  Redraw fully using HDswell\n",
      "Assuming we have run the previous canSwell block.  This block repeats the code, but starting from the home unit\n",
      "This takes 1 - 1000 sec per HD :-( The total number of HDs to fix is 22\n",
      "swell-generating HD 1055 our 1 th HD we must regrow out of 22 0 sec elapsed\n",
      "swell-generating HD 1233 our 11 th HD we must regrow out of 22 5 sec elapsed\n",
      "swell-generating HD 1979 our 21 th HD we must regrow out of 22 12 sec elapsed\n"
     ]
    }
   ],
   "source": [
    "#THIS IS THE MUSTSPAWN code block - stolen from vanillaHD-OHredo\n",
    "print(\"And now, the major disco'd HDs (< 0.75 aDP in HDcP-contig portion and/or enclaves).  Redraw fully using HDswell\")\n",
    "print(\"Assuming we have run the previous canSwell block.  This block repeats the code, but starting from the home unit\")\n",
    "print(\"This takes 1 - 1000 sec per HD :-( The total number of HDs to fix is\",len(badDiscoList))\n",
    "#avgDiam = MAP.area**0.5 / float(nDistricts)\n",
    "startTime = time.time()\n",
    "for i,t in enumerate(badDiscoList):\n",
    "    if i%10 == 0:\n",
    "        print(\"swell-generating HD\",t,\"our\",i+1,\"th HD we must regrow out of\",len(badDiscoList),int(time.time()-startTime),\"sec elapsed\" )\n",
    "    notInCluster = True\n",
    "    for jj, geo in enumerate(CCBgeom):  #swell in-corner HDs from the corner cluster\n",
    "        if geo.contains(hdCP[t]):\n",
    "            starterU = allUnits.index(jj+0.25)\n",
    "            notInCluster = False\n",
    "    if notInCluster:\n",
    "        starterU = homeU[t]\n",
    "        #distList = [hdCP[t].distance(unitCP[u]) for u in HDunitList[t] ]\n",
    "        #starterU = HDunitList[t][distList.index(np.min(distList))]  #starter = unit with centroid closest to the hd center\n",
    "    contigUs = [starterU]  #we used getContigFromStarter(starterU, HDvtdList[t], unitNbrs) in above code block\n",
    "    contigPop = np.sum( [ unitPop[u] for u in contigUs ] )\n",
    "    gap = aDP - contigPop\n",
    "    origGap = gap\n",
    "    currList, addedList = contigUs.copy(), list()\n",
    "    adjoiners = list( set( getAdjoiners(currList, unitNbrs) ).difference(wholeSet) )\n",
    "    nearHDlist = [uu for uu in adjoiners]  #bias toward underused, close to HD (and its center)\n",
    "    #                                            subbed HDcircle for HDpoly in below\n",
    "    nearHDscore = [ (0.2*(unitUse[uu] - 1.) ) + 0.5*(unitCP[uu].distance(HDcircle[t]) + \n",
    "        unitCP[uu].distance(hdCP[t])  )  / HDdiam[t] for uu in adjoiners ]\n",
    "    stillGoing = True\n",
    "    \n",
    "    while gap > maxGap and len(nearHDlist) > 0 and stillGoing:   #add the lowest-scoring neighboring underused unit until we've roughly squared the HDpop\n",
    "        idx, i, notYetPicked = np.argsort(nearHDscore), 0, True\n",
    "        while i < len(nearHDscore) and notYetPicked:        \n",
    "            listNo = idx[i]   #nearHDscore.index(np.min(nearHDscore))\n",
    "            unitNoToAdd = nearHDlist[listNo]  #add this unit ...\n",
    "            canAdd  = wontEnclave(unitNoToAdd, currList, unitNbrs, borderUnits)\n",
    "            if canAdd:\n",
    "                notYetPicked = False\n",
    "            else:\n",
    "                i +=1\n",
    "        if notYetPicked:\n",
    "            stillGoing = False  #can't add any more units without creating an enclave\n",
    "        else: #we selected the best unit to add legally\n",
    "            gap -= unitPop[unitNoToAdd]\n",
    "            addedList.append(unitNoToAdd)\n",
    "            currList.append( unitNoToAdd)\n",
    "            for uu in unitNbrs[unitNoToAdd]: # ... and add its nonHD, nonwhole neighbors to future candidates\n",
    "                if uu not in currList and uu not in nearHDlist and unitPop[uu] < gap + maxGap and uu not in wholeSet:  \n",
    "                    nearHDlist.append(uu)                           #subbed HDcircle for HDpoly in below\n",
    "                    nearHDscore.append((0.1*(unitUse[uu] - 1.) ) + 0.5*(unitCP[uu].distance(HDcircle[t]) + \n",
    "                                                                        unitCP[uu].distance(hdCP[t])  )  / HDdiam[t] )\n",
    "            del nearHDscore[nearHDlist.index(unitNoToAdd)]        \n",
    "            del nearHDlist[ nearHDlist.index(unitNoToAdd) ]\n",
    "            for i, uu in enumerate(nearHDlist.copy()):\n",
    "                if unitPop[uu] > gap + maxGap:   #with the added pop from another unit, this unit is now too big to add\n",
    "                    del nearHDscore[nearHDlist.index(uu)]\n",
    "                    del nearHDlist[ nearHDlist.index(uu)]\n",
    "    for u in addedList:\n",
    "        unitUse[u] += HDweight[t] * nDistricts\n",
    "    for u in list( set(HDunitList[t]).difference(set(contigUs)) ):\n",
    "        unitUse[u] -= HDweight[t] * nDistricts       \n",
    "    HDunitList[t] = contigUs + addedList\n",
    "    HDvPop[t]    = np.sum( [unitPop[u] for u in HDunitList[t] ] )\n",
    "    HDnAddedUnits[t] = len(addedList)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "id": "1056f787-fcb6-4927-965a-54abfe4b59ce",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "update classification of HDs by contiguity\n",
      "quick classification: who has contiguity problems?\n",
      "working on HD 0 time is now 0\n",
      "working on HD 700 time is now 4\n",
      "working on HD 1402 time is now 7\n",
      "working on HD 2102 time is now 10\n",
      "working on HD 2802 time is now 15\n",
      "working on HD 3503 time is now 18\n",
      "working on HD 4204 time is now 21\n",
      "working on HD 4906 time is now 24\n",
      "working on HD 5606 time is now 28\n",
      "working on HD 6306 time is now 32\n",
      "working on HD 7006 time is now 36\n",
      "working on HD 7706 time is now 38\n",
      "working on HD 8407 time is now 44\n",
      "out of 8934 total HDs, there were 8934.0 contiguous and 8934.0 complement-contiguous HDs\n",
      "0 HDs had both discontiguity problems, while enclave-only = 0 and discontig only= 0\n"
     ]
    }
   ],
   "source": [
    "print(\"update classification of HDs by contiguity\") #take from vanillaHD\n",
    "\n",
    "### THIS IS THE \"FIND DISCO\" CODE\n",
    "print(\"quick classification: who has contiguity problems?\")\n",
    "nUnbroken, nNoEnclave, smallPieceLists, enclaveLists, sPgenerator, eLgenerator = 0., 0., list(), list(), list(), list()\n",
    "smallPieceLengths, enclaveLengths = list(), list()\n",
    "doubleTroubleList = list()\n",
    "startTime = time.time()\n",
    "for i,t in enumerate(popHDlist):\n",
    "    if i%700 == 0:\n",
    "        print(\"working on HD\",t,\"time is now\",int(time.time() - startTime) )\n",
    "    unbroken, noEnclave,smallPieceList,enclaveList = enclaveCheck(HDunitList[t], unitNbrs,4) #,6) #6 is high (slow) to try to avoid false enclaves\n",
    "    if unbroken:\n",
    "        nUnbroken +=1\n",
    "    if noEnclave:\n",
    "        nNoEnclave +=1\n",
    "    if not unbroken:\n",
    "        smallPieceLists.append(smallPieceList)\n",
    "        smallPieceLengths.append(len(smallPieceList))\n",
    "        sPgenerator.append(t)\n",
    "    if not noEnclave and unbroken:   #district is contiguous but contains 1+ enclave\n",
    "        enclaveLists.append(enclaveList)\n",
    "        enclaveLengths.append(len(enclaveList))\n",
    "        eLgenerator.append(t)\n",
    "    if not noEnclave and not unbroken:  #extremely discontig (\"broken\") HDs can appear to have enclaves;\n",
    "        doubleTroubleList.append(t)\n",
    "print(\"out of\",len(popHDlist),\"total HDs, there were\",nUnbroken,\"contiguous and\",nNoEnclave,\"complement-contiguous HDs\")\n",
    "print(len(doubleTroubleList),\"HDs had both discontiguity problems, while enclave-only =\",len(eLgenerator),\n",
    "      \"and discontig only=\",len(sPgenerator)-len(doubleTroubleList) )\n",
    "\n",
    "if len(smallPieceLists) + len(enclaveLists) > 0:\n",
    "    print(\"here are the histograms of the small piece and enclave list lengths, total no =\",\n",
    "          len(smallPieceLists),len(enclaveLists) )\n",
    "    plt.hist([s for s in smallPieceLengths],label=\"small piece l units\",histtype='step',\n",
    "             cumulative=True,bins=[0,1,2,3,4,5,6,8,10,12,15,20,25,30,35,40,45,50,60,80,120,200])\n",
    "    plt.hist([e for e in enclaveLengths],label=\"enclave l units\",histtype='step',\n",
    "             cumulative=True,bins=[0,1,2,3,4,5,6,8,10,12,15,20,25,30,35,40,45,50,60,80,120,200])\n",
    "    plt.legend()\n",
    "    plt.show()\n",
    "    print(\"And here are the small-HD-piece and small-enclave pops\")\n",
    "    plt.hist([sum(unitPop[u] for u in s) for s in smallPieceLists],label=\"small piece 1 pop\",histtype='step')\n",
    "    plt.hist([sum(unitPop[u] for u in e) for e in enclaveLists],label=\"enclave 1 pop\",histtype='step')\n",
    "    plt.legend()\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "id": "6a132d0c-ec17-41cc-badf-7f466d990ee3",
   "metadata": {},
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1354 292161\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist([HDvPop[t] for t in popHDlist])\n",
    "plt.axvline(aDP,ls=\"--\")\n",
    "plt.show()\n",
    "for t in popHDlist:\n",
    "    if HDvPop[t] < 0.6*aDP:\n",
    "        print(t,HDvPop[t])\n",
    "        plotPoly(HDCP[t].buffer(0.01))\n",
    "#plotPoly(countyGeom[47])\n",
    "plt.show()\n",
    "for t in eLgenerator:\n",
    "    print(\"enclavy\",t,HDvPop[t])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "id": "61a68747-7cb9-4048-b63b-b23a22309929",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1055, 1095, 1522, 1572, 2049, 8646, 1803, 1356, 2062, 3216, 1233, 2002, 1494, 1559, 7706, 2972, 2216, 5481, 1980, 1778, 1979, 6076]\n"
     ]
    }
   ],
   "source": [
    "print(badDiscoList)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "id": "3f2caed4-154e-49e2-a2ed-772b61c9e19b",
   "metadata": {},
   "outputs": [],
   "source": [
    "nonsquaredHDlist = [HDunitList[t].copy() for t in range(nHDs)]  #safekeeping"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 235,
   "id": "1d0dcc8a-d0fc-48a9-bc6c-64d6041c288f",
   "metadata": {},
   "outputs": [],
   "source": [
    "#HDunitList[t] = latestHDlist[t].copy() #restart\n",
    "#HDvPop = [np.sum([unitPop[u] for u in HDunitList[t] ]) for t in range(nHDs) ]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "id": "6b3dd3ff-706e-4e0d-a705-3a82cd62b519",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "We will now square up the 2000 HDs with pop < 782696 to within 1195\n",
      "working on squaring up HD 12 time is now 0\n",
      "working on squaring up HD 474 time is now 51\n",
      "working on squaring up HD 1198 time is now 64\n",
      "working on squaring up HD 1785 time is now 66\n",
      "working on squaring up HD 2116 time is now 90\n",
      "working on squaring up HD 2571 time is now 117\n",
      "working on squaring up HD 2806 time is now 223\n",
      "working on squaring up HD 3169 time is now 255\n",
      "working on squaring up HD 3666 time is now 267\n",
      "working on squaring up HD 3972 time is now 274\n",
      "working on squaring up HD 4327 time is now 279\n",
      "working on squaring up HD 4815 time is now 280\n",
      "working on squaring up HD 5189 time is now 282\n",
      "working on squaring up HD 5787 time is now 287\n",
      "working on squaring up HD 6307 time is now 319\n",
      "working on squaring up HD 6801 time is now 345\n",
      "working on squaring up HD 7285 time is now 347\n",
      "working on squaring up HD 7794 time is now 350\n",
      "working on squaring up HD 8086 time is now 375\n",
      "working on squaring up HD 8378 time is now 400\n",
      "We have attempted to address underpop in a total of 2000 HDs\n",
      "Here is a scatterplot of original (x) to final pop (y)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#SQUARING UP UNDERPOPPED\n",
    "HDnAddedUnits, HDaddedPop = [0]*nHDs, [0.]*nHDs\n",
    "underPoppedList, stillUnderPoppedList = list(),list()\n",
    "minDistrictPop, maxDistrictPop = 0.995 * aDP, 1.005 * aDP\n",
    "for t,pop in enumerate(HDvPop):\n",
    "    if pop < minDistrictPop and t in popHDlist:\n",
    "        underPoppedList.append(t)\n",
    "maxGap = 0.9 * np.median(unitPop)  #maxDistrictPop - aDP \n",
    "print(\"We will now square up the\",len(underPoppedList),\"HDs with pop <\",int(minDistrictPop),\"to within\",int(maxGap) )\n",
    "startTime = time.time()\n",
    "for ii,t in enumerate(underPoppedList):\n",
    "    if ii%100 == 0:\n",
    "        print(\"working on squaring up HD\",t,\"time is now\",int(time.time() - startTime)) \n",
    "    gap = aDP - HDvPop[t]\n",
    "    origGap = gap\n",
    "    nearHDlist, nearHDscore = list(), list()  #these will be dynamic lists of the nearby underused units\n",
    "    for u in HDunitList[t]:\n",
    "        for uu in unitNbrs[u]:\n",
    "            if uu not in HDunitList[t] and uu not in nearHDlist and unitPop[uu] < gap + maxGap and uu not in wholeSet:\n",
    "                nearHDlist.append(uu)   #below line: bias toward close, underused\n",
    "                nearHDscore.append((unitUse[uu]-1.) + unitCP[uu].distance(hdCP[t]) / avgDist[t] )  \n",
    "    currList = HDunitList[t].copy()\n",
    "    addedList = list()\n",
    "    stillGoing = True\n",
    "    while gap > maxGap and len(nearHDlist) > 0 and stillGoing:   #add the lowest-scoring neighboring underused unit until we've roughly squared the HDpop\n",
    "        idx, i, notYetPicked = np.argsort(nearHDscore), 0, True\n",
    "        while i < len(nearHDscore) and notYetPicked:        \n",
    "            listNo = idx[i]   #nearHDscore.index(np.min(nearHDscore))\n",
    "            unitNoToAdd = nearHDlist[listNo]  #add this unit ...\n",
    "            canAdd  = wontEnclave(unitNoToAdd, currList, unitNbrs, borderUnits)\n",
    "            if canAdd: \n",
    "                notYetPicked = False\n",
    "            else:\n",
    "                i +=1\n",
    "        if notYetPicked:\n",
    "            stillGoing = False  #can't add any more units without creating an enclave\n",
    "        else:\n",
    "            gap -= unitPop[unitNoToAdd]\n",
    "            addedList.append(unitNoToAdd)\n",
    "            currList.append( unitNoToAdd)\n",
    "            for uu in unitNbrs[unitNoToAdd]:             # ... and add its nonHD neighbors to future candidates\n",
    "                if uu not in currList and uu not in nearHDlist and unitPop[uu] < gap + maxGap and uu not in wholeSet:  \n",
    "                    nearHDlist.append(uu)\n",
    "                    nearHDscore.append((unitUse[uu]-1.) + unitCP[uu].distance(hdCP[t]) / avgDist[t] )  #bias toward close, underused\n",
    "            del nearHDscore[nearHDlist.index(unitNoToAdd)]        \n",
    "            del nearHDlist[ nearHDlist.index(unitNoToAdd) ]\n",
    "            for i, uu in enumerate(nearHDlist.copy()):\n",
    "                if unitPop[uu] > gap + maxGap:   #with the added pop from another unit, this unit is now too big to add\n",
    "                    del nearHDscore[nearHDlist.index(uu)]\n",
    "                    del nearHDlist[ nearHDlist.index(uu)]\n",
    "    for u in addedList:\n",
    "        unitUse[u] += HDweight[t] * nDistricts\n",
    "    HDunitList[t] += addedList\n",
    "    HDvPop[t]    = np.sum( [unitPop[u] for u in HDunitList[t] ] )\n",
    "    HDnAddedUnits[t] = len(addedList)\n",
    "    HDaddedPop[t] = np.sum( [unitPop[u] for u in addedList] )\n",
    "    if HDvPop[t] > maxDistrictPop:\n",
    "        print(\"Oops! HD\",t,\"now has overshot pop =\",int(HDvPop[t]),\"not\",int(aDP),\"after adding\",HDaddedPop[t] )\n",
    "    if HDvPop[t] < minDistrictPop:\n",
    "        stillUnderPoppedList.append(t)\n",
    "print(\"We have attempted to address underpop in a total of\",len(underPoppedList),\"HDs\")\n",
    "if len(stillUnderPoppedList) > 0:\n",
    "    print(\"... but we got stuck in\",len(stillUnderPoppedList))\n",
    "print(\"Here is a scatterplot of original (x) to final pop (y)\")\n",
    "plt.scatter([HDvPop[t] - HDaddedPop[t] for t in underPoppedList], [HDvPop[t] for t in underPoppedList])\n",
    "plt.axhline(y=aDP, xmin = 0.9*aDP, xmax = 1.1*aDP, ls=\"--\")\n",
    "plt.axvline(x=aDP, ymin = 0.9*aDP, ymax = 1.1*aDP, ls=\"--\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "id": "72398364-3e4a-4a03-a2cf-58a21bdea412",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "previous unit avg and sd usage are 1.01339 0.1048\n",
      "amped unit avg and sd usage are 1.02332 0.10045\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "prevUnitUse = [0.]*nUnits\n",
    "for t in popHDlist:\n",
    "    for u in latestHDlist[t]:\n",
    "        prevUnitUse[u] += HDweight[t] * nDistricts\n",
    "\n",
    "ampedUnitUse = [0. for u in range(nUnits)]\n",
    "ampedHDlist = [HDunitList[t].copy() for t in range(nHDs)]\n",
    "ampedHDpop = [HDvPop[t] for t in range(nHDs) ]\n",
    "for t in popHDlist:\n",
    "    for u in ampedHDlist[t]:\n",
    "        ampedUnitUse[u] += HDweight[t] * nDistricts   #KISS - recalc these\n",
    "plt.hist(prevUnitUse,bins=50,weights=unitPop,label=\"previous\",histtype=\"step\")\n",
    "plt.hist(ampedUnitUse, bins=50, weights=unitPop,label=\"amped\",histtype=\"step\")\n",
    "plt.legend()\n",
    "ampedUnitUseAvg, ampedUnitUseSD = getWeightedAvgAndSD(ampedUnitUse,unitPop)\n",
    "print(\"previous unit avg and sd usage are\",r5(latestAvg), r5(latestSD) )\n",
    "print(\"amped unit avg and sd usage are\",r5(ampedUnitUseAvg), r5(ampedUnitUseSD) )\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "98046bb5-db38-4730-869b-2c6512754b36",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "id": "f703cd30-fc17-4e4e-a458-40d9c74b266b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Continuing with narrowing the distro.  This loop: remove overused units from overpopped HDs\n",
      "Let's now square down the 5032 overPopped HDs to within 1195\n",
      "working on squaring down HD 0 time is now 0\n",
      "working on squaring down HD 347 time is now 39\n",
      "working on squaring down HD 645 time is now 94\n",
      "working on squaring down HD 929 time is now 117\n",
      "working on squaring down HD 1243 time is now 153\n",
      "working on squaring down HD 1575 time is now 162\n",
      "working on squaring down HD 2021 time is now 196\n",
      "working on squaring down HD 2400 time is now 268\n",
      "working on squaring down HD 2690 time is now 296\n",
      "working on squaring down HD 3127 time is now 315\n",
      "working on squaring down HD 3489 time is now 329\n",
      "working on squaring down HD 3874 time is now 348\n",
      "working on squaring down HD 4229 time is now 355\n",
      "working on squaring down HD 4542 time is now 367\n",
      "working on squaring down HD 4902 time is now 387\n",
      "working on squaring down HD 5269 time is now 403\n",
      "working on squaring down HD 5596 time is now 428\n",
      "working on squaring down HD 5909 time is now 475\n",
      "working on squaring down HD 6257 time is now 514\n",
      "working on squaring down HD 6584 time is now 542\n",
      "working on squaring down HD 6924 time is now 579\n",
      "can't drop any more units to HD 7133 without creating an enclave\n",
      "working on squaring down HD 7328 time is now 585\n",
      "working on squaring down HD 7669 time is now 594\n",
      "working on squaring down HD 8161 time is now 625\n",
      "working on squaring down HD 8582 time is now 647\n",
      "working on squaring down HD 8895 time is now 661\n",
      "We have attempted to address underpop in a total of 5032 HDs\n",
      "Here is a scatterplot of original to final pop\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#SQUARING DOWN\n",
    "print(\"Continuing with narrowing the distro.  This loop: remove overused units from overpopped HDs\")\n",
    "HDnShedUnits = [0]*nHDs\n",
    "overPoppedList, stillOverPoppedList = list(), list()\n",
    "startTime = time.time()\n",
    "for t,pop in enumerate(HDvPop):\n",
    "    if pop > maxDistrictPop and t in popHDlist:\n",
    "        overPoppedList.append(t)\n",
    "\n",
    "maxGap = 0.9 * np.median(unitPop)  # = aDP - minDistrictPop   \n",
    "print(\"Let's now square down the\",len(overPoppedList),\"overPopped HDs to within\", int(maxGap))   \n",
    "for ii,t in enumerate(overPoppedList):\n",
    "    if ii%200 == 0:\n",
    "        print(\"working on squaring down HD\",t,\"time is now\",int(time.time()-startTime))\n",
    "    unbroken, noEnclave, sPL, ePL = enclaveCheck(HDunitList[t],unitNbrs)\n",
    "    if not (unbroken and noEnclave):\n",
    "        print(\"SKIPPING shedding attempt on overpopped HD\",t,\"with pop\",HDvPop[t],\"because it was not legal to start\")\n",
    "    else:\n",
    "        excess = HDvPop[t] - aDP\n",
    "        origExcess = excess\n",
    "        HDboundaryList, HDboundaryScore = list(), list()  #these will be dynamic lists of the overused border units to jettison\n",
    "        #distList = [hdCP[t].distance(unitCP[u]) for u in HDunitList[t] ]\n",
    "        starterU = homeU[t] #HDunitList[t][distList.index(np.min(distList))] #update from vanillaHD\n",
    "        barredSet = barredJettisonSet.union({starterU})\n",
    "        for u in set(HDunitList[t]).difference(barredSet):\n",
    "            isBoundary = False\n",
    "            for uu in unitNbrs[u]:\n",
    "                if uu not in HDunitList[t]:\n",
    "                    isBoundary = True\n",
    "                    break\n",
    "            if isBoundary and HDvPop[t] - unitPop[u] > aDP - maxGap:  #shedding this unit won't send us too far under targetpop\n",
    "                HDboundaryList.append(u)\n",
    "                HDboundaryScore.append((1. - unitUse[u]) - unitCP[u].distance(hdCP[t]) / avgDist[t])  #low-score = bias toward far, overused\n",
    "        currList = HDunitList[t].copy()\n",
    "        shedList, stillGoing = list(), True\n",
    "        while excess > maxGap and len(HDboundaryList) > 0 and stillGoing:   #shed the highest-scoring neighboring overused unit until we've roughly squared the HDpop\n",
    "            idx, i, notYetPicked = np.argsort(HDboundaryScore), 0, True\n",
    "            while i < len(HDboundaryScore) and notYetPicked and stillGoing:        \n",
    "                listNo = idx[i]   #low (large negative) score is preferred to shed\n",
    "                unitNoToShed = HDboundaryList[listNo]  # attempt to shed this unit ...\n",
    "                tryList = list(set(currList).difference( {unitNoToShed} ) )\n",
    "                unbroken, noEnclave, sPL, ePL = enclaveCheck(tryList,unitNbrs) \n",
    "                if unbroken and noEnclave:             #... if that won't eff up contiguity\n",
    "                    notYetPicked = False\n",
    "                else:\n",
    "                    i +=1\n",
    "            if notYetPicked:\n",
    "                stillGoing = False  #can't drop any more units without creating an enclave\n",
    "                print(\"can't drop any more units to HD\",t,\"without creating an enclave\")\n",
    "            else: #add this eligible unit\n",
    "                shedList.append(unitNoToShed)\n",
    "                excess -= unitPop[unitNoToShed]        \n",
    "                del currList[currList.index(unitNoToShed) ]\n",
    "                del HDboundaryList[listNo]\n",
    "                del HDboundaryScore[listNo]\n",
    "                for u in unitNbrs[unitNoToShed]:      # ... and ID any neighboring units that will now be on boundary after we shed this unit\n",
    "                    if u in currList and u not in HDboundaryList and (unitPop[u] <= excess + maxGap and u not in barredSet): \n",
    "                        HDboundaryList.append(u)\n",
    "                        HDboundaryScore.append( (1. - unitUse[u]) - unitCP[u].distance(hdCP[t]) / avgDist[t] )  #low-score, bias toward far & overused       \n",
    "                for uu in HDboundaryList.copy():\n",
    "                    if unitPop[uu] > excess + maxGap:  #checking to see if the latest pop change DQ's any large units on current boundary\n",
    "                        del HDboundaryScore[HDboundaryList.index(uu)]\n",
    "                        del HDboundaryList[HDboundaryList.index(uu)]   \n",
    "        for u in shedList:\n",
    "            unitUse[u] -= HDweight[t] * nDistricts\n",
    "        HDunitList[t], HDvPop[t] = currList.copy(), np.sum( [unitPop[u] for u in currList ] )    \n",
    "        if HDvPop[t] < minDistrictPop:\n",
    "            print(\"Oops! HD\",t,\"now has undershot pop =\",int(HDvPop[t]),\"not\",int(aDP),\"after shedding\",\n",
    "                 np.sum([unitPop[u] for u in shedList]) )        \n",
    "        if HDvPop[t] < minDistrictPop:\n",
    "            stillOverPoppedList.append(t)\n",
    "        HDnShedUnits[t] = -1 * len(shedList)\n",
    "        if homeU[t] not in HDunitList[t]:\n",
    "            print(\"WARNING: we lost the home unit\",homeU[t],\"from HD\",HD)\n",
    "            lostHomeUlist.append(t)\n",
    "            \n",
    "print(\"We have attempted to address underpop in a total of\",len(overPoppedList),\"HDs\")\n",
    "if len(stillOverPoppedList) > 0:\n",
    "    print(\"... but we got stuck in\",len(stillOverPoppedList))\n",
    "print(\"Here is a scatterplot of original to final pop\")\n",
    "plt.scatter([ampedHDpop[t] for t in overPoppedList], [HDvPop[t] for t in overPoppedList])\n",
    "plt.axhline(aDP, 0.9*aDP, 1.1*aDP, ls=\"--\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "id": "dbf01e05-ce50-4615-9adc-1ab0d902c097",
   "metadata": {},
   "outputs": [],
   "source": [
    "minDistrictPop, maxDistrictPop = 0.995*aDP, 1.005*aDP"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "id": "9c4d12b3-8596-4a5b-937e-7ef8ed71a903",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "updating our unitUse, underpopped and overpopped lists\n",
      "unit use histogram\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "unit use by pop\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "we now have a total of 0 underpopped HDs and 82 overpopped HDs\n"
     ]
    }
   ],
   "source": [
    "print(\"updating our unitUse, underpopped and overpopped lists\")\n",
    "unitUse = [0.]*nUnits\n",
    "HDvPop = [0.]*nHDs\n",
    "stillUnder, stillOver = list(), list()\n",
    "for t in popHDlist:\n",
    "    if homeU[t] not in HDunitList[t]:\n",
    "        print(\"WARNING - we lost home unit\",homeU[t],\"from HD\",t)\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += nDistricts * HDweight[t]\n",
    "        HDvPop[t] += unitPop[u]\n",
    "    if HDvPop[t] < minDistrictPop:\n",
    "        stillUnder.append(t)\n",
    "    if HDvPop[t] > maxDistrictPop:\n",
    "        stillOver.append(t)\n",
    "print(\"unit use histogram\")\n",
    "plt.hist(unitUse, weights = unitPop)\n",
    "plt.show()\n",
    "print(\"unit use by pop\")\n",
    "plt.scatter(unitPop,unitUse)\n",
    "plt.show()\n",
    "print(\"we now have a total of\",len(stillUnder),\"underpopped HDs and\",len(stillOver),\"overpopped HDs\")\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "id": "68490ecd-8d53-44f0-b7fd-0df71cce9d27",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "intermediate save to file -- still to address under-overpops\n"
     ]
    }
   ],
   "source": [
    "print(\"intermediate save to file -- still to address under-overpops\")\n",
    "HDvPop = [0. for t in range(nHDs)]  #writing UNIT lists to a file\n",
    "tList = [t for t in range(nHDs)]\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        HDvPop[t] += unitPop[u]\n",
    "outDF = pd.DataFrame( {\"tract\":tList,\"HDweight\":HDweight,\"HDvPop\":HDvPop,\"HDunitList\":HDunitList,\n",
    "                      \"centroid x\":HDCPx, \"centroid y\":HDCPy, \"homeU\":homeU, \"homeC\":homeC} )\n",
    "outname = STATE+str(int(nHDs))+\"COI615mostlyGoodPop.csv\" #\"contigUnpatchedB.csv\" unpatchedContigGoodPop.csv\n",
    "outpath = \"2024state_HD_output/\"+outname\n",
    "outDF.to_csv(outpath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "839d5b87-3dd7-46a0-a119-febf5b6fd99f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "optional restart.  Read in temp-saved HDunitlists.  Then the unit topology\n",
      "I read in a total of 8941 home district unit lists, of which 8934 are populated\n"
     ]
    }
   ],
   "source": [
    "print(\"optional restart.  Read in temp-saved HDunitlists.  Then the unit topology\")\n",
    "inDF = pd.read_csv(\"./2024state_HD_output/OH8941COI615mostlyGoodPop.csv\")\n",
    "HDweight, homeU, homeC = inDF[\"HDweight\"],inDF[\"homeU\"],inDF[\"homeC\"]\n",
    "nHDs = len(HDweight)\n",
    "popHDlist = list()\n",
    "for h in range(nHDs):\n",
    "    if HDweight[h] > 0:\n",
    "        popHDlist.append(h)\n",
    "unitString = inDF[\"HDunitList\"]\n",
    "HDunitList = [ast.literal_eval(unitString[h]) for h in range(nHDs)]\n",
    "print(\"I read in a total of\",nHDs,\"home district unit lists, of which\",len(popHDlist),\"are populated\")\n",
    "HDvPop = inDF[\"HDvPop\"]\n",
    "HDCPx, HDCPy = inDF[\"centroid x\"],inDF[\"centroid y\"]\n",
    "HDCP = [Point(HDCPx[h],HDCPy[h]) for h in range(nHDs)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "e10337fd-e30f-45fa-9299-83c1e5fc34d7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "optional restart continued ... read in the bg and unit topology\n"
     ]
    }
   ],
   "source": [
    "print(\"optional restart continued ... read in the bg and unit topology\")\n",
    "nbrDF = pd.read_csv(\"./state_map_files/OH99COI615-unitTopologiesBG_17Nov.csv\")\n",
    "unitPop, unitCPx, unitCPy = nbrDF[\"unitPop\"],nbrDF[\"centroid x\"],nbrDF[\"centroid y\"]\n",
    "nUnits = len(unitPop)\n",
    "unitCP = [Point(unitCPx[u],unitCPy[u]) for u in range(nUnits)]\n",
    "onBorder, cantSplit = nbrDF[\"onBorder\"],nbrDF[\"cantSplit\"]\n",
    "borderUnits = list()\n",
    "for u in range(nUnits):\n",
    "    if onBorder[u] == 1:\n",
    "        borderUnits.append(u)\n",
    "unitNbrString = nbrDF[\"unitNbrs\"]\n",
    "unitNbrs = [ast.literal_eval(unitNbrString[u]) for u in range(nUnits)]\n",
    "\n",
    "unsplittableUnits = list()\n",
    "for u in range(nUnits):\n",
    "    if cantSplit[u] == 1:\n",
    "        unsplittableUnits.append(u)\n",
    "unitCountyNo, unitTLstring = nbrDF[\"unitCountyNo\"],nbrDF[\"unitTractList\"]\n",
    "countyUnitList = [list() for c in range(nCounties)]\n",
    "for u in range(nUnits):\n",
    "    countyUnitList[unitCountyNo[u]].append(u)\n",
    "unitTractList = [ast.literal_eval(unitTLstring[u]) for u in range(nUnits) ]\n",
    "\n",
    "bgDF = pd.read_csv(\"./state_map_files/OH99mod_bgTopologies_17Nov24.csv\")\n",
    "tractPop, tractCPx, tractCPy = bgDF[\"bgPop\"],bgDF[\"centroid x\"],bgDF[\"centroid y\"]\n",
    "nTracts = len(tractPop)\n",
    "tractCP = [Point(tractCPx[b],tractCPy[b]) for b in range(nTracts)]\n",
    "bgNbrString = bgDF[\"bgNbrs\"]\n",
    "bgNbrs = [ast.literal_eval(bgNbrString[b]) for b in range(nTracts)]\n",
    "countyNo,isBorderBG = bgDF[\"countyNo\"],bgDF[\"isBorderBG\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "86aad656-b6db-47b7-b7c1-3e707f4fe8e6",
   "metadata": {},
   "outputs": [],
   "source": [
    "for h in range(nHDs):\n",
    "    sumPop = np.sum([unitPop[u] for u in HDunitList[h]])\n",
    "    if abs(sumPop - HDvPop[h]) > 1000:\n",
    "        print(h)"
   ]
  },
  {
   "cell_type": "raw",
   "id": "35aa9920-4518-404f-9480-675b12e1f0ab",
   "metadata": {},
   "source": [
    "print(\"upon restart, rebuild the unit geoms\")\n",
    "unitGeom = list()\n",
    "for u in range(nUnits):\n",
    "    if u%800 == 0:\n",
    "        print(\"rebuilding unit geom for unit\",u)\n",
    "    unitGeom.append(tractGeom[unitTractList[u][0]] )\n",
    "    for b in unitTractList[u]:\n",
    "        unitGeom[u] = unitGeom[u].union(tractGeom[b])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "id": "158ffada-288a-4574-8180-24f7c68cacd2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "updating our unitUse, underpopped and overpopped lists\n",
      "unit use histogram\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "unit use by pop\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "we now have a total of 0 underpopped HDs and 82 overpopped HDs\n"
     ]
    }
   ],
   "source": [
    "print(\"updating our unitUse, underpopped and overpopped lists\")\n",
    "minDistrictPop, maxDistrictPop = 0.995*aDP, 1.005*aDP\n",
    "unitUse = [0.]*nUnits\n",
    "HDvPop = [0.]*nHDs\n",
    "stillUnder, stillOver = list(), list()\n",
    "for t in popHDlist:\n",
    "    if homeU[t] not in HDunitList[t]:\n",
    "        print(\"WARNING - we lost home unit\",homeU[t],\"from HD\",t)\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += nDistricts * HDweight[t]\n",
    "        HDvPop[t] += unitPop[u]\n",
    "    if HDvPop[t] < minDistrictPop:\n",
    "        stillUnder.append(t)\n",
    "    if HDvPop[t] > maxDistrictPop:\n",
    "        stillOver.append(t)\n",
    "print(\"unit use histogram\")\n",
    "plt.hist(unitUse, weights = unitPop)\n",
    "plt.show()\n",
    "print(\"unit use by pop\")\n",
    "plt.scatter(unitPop,unitUse)\n",
    "plt.show()\n",
    "print(\"we now have a total of\",len(stillUnder),\"underpopped HDs and\",len(stillOver),\"overpopped HDs\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "id": "c7b7fff8-d72b-48b6-a1f3-e131d23f1adb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAjgAAAGdCAYAAAAfTAk2AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjguMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/H5lhTAAAACXBIWXMAAA9hAAAPYQGoP6dpAAAdu0lEQVR4nO3df3DX9X3A8VcwJEAhCT8kgZoIPa2oCFWomGm7TrNmjOt00s312Ead104XnUivVbZW1t62cHan1h5i17Ww3WpZ2Q1bq+I4VFw7QIlSQSzViYMrJrR1JEAlIHnvD8/v+ZVfCQkE3z4ed9878/m88/2+8r6vfJ/3zff7TUlKKQUAQEYG9PcAAAB9TeAAANkROABAdgQOAJAdgQMAZEfgAADZETgAQHYEDgCQndL+HuCdurq6YseOHTFs2LAoKSnp73EAgG5IKcXu3btj7NixMWBA/z9/csoFzo4dO6K2tra/xwAAjsP27dvjjDPO6O8xTr3AGTZsWES8uUEVFRX9PA0A0B0dHR1RW1tbeBzvb6dc4Lz1a6mKigqBAwDvMqfKy0v6/5dkAAB9TOAAANkROABAdgQOAJAdgQMAZEfgAADZETgAQHYEDgCQHYEDAGRH4AAA2RE4AEB2BA4AkB2BAwBkR+AAANkp7e8BAODdbNxtD/X3CD32yoIZ/T3CCecZHAAgOwIHAMiOwAEAsiNwAIDsCBwAIDsCBwDIjsABALIjcACA7AgcACA7AgcAyI7AAQCyI3AAgOwIHAAgOwIHAMiOwAEAsiNwAIDsCBwAIDsCBwDIjsABALIjcACA7AgcACA7AgcAyI7AAQCyI3AAgOwIHAAgOwIHAMiOwAEAsiNwAIDsCBwAIDsCBwDIjsABALIjcACA7AgcACA7AgcAyE6vAmfBggVRUlISc+bMKRzbt29fNDU1xciRI2Po0KExc+bMaGtr6+2cAADddtyB8/TTT8c3vvGNmDRpUtHxW265JR588MFYtmxZrF69Onbs2BFXX311rwcFAOiu4wqcPXv2xKxZs+Kb3/xmDB8+vHC8vb09vvWtb8Wdd94Zl19+eUyZMiUWL14c//3f/x1r167ts6EBAI7muAKnqakpZsyYEQ0NDUXHW1pa4sCBA0XHJ0yYEHV1dbFmzZrDXldnZ2d0dHQUXQAAeqO0p9+wdOnSeOaZZ+Lpp58+5Fxra2uUlZVFVVVV0fHq6upobW097PU1NzfHl7/85Z6OAQBwRD16Bmf79u1x8803x3e+850YNGhQnwwwb968aG9vL1y2b9/eJ9cLALx39ShwWlpaYufOnXHRRRdFaWlplJaWxurVq+Oee+6J0tLSqK6ujv3798euXbuKvq+trS1qamoOe53l5eVRUVFRdAEA6I0e/YrqiiuuiI0bNxYdu/baa2PChAlx6623Rm1tbQwcODBWrVoVM2fOjIiILVu2xLZt26K+vr7vpgYAOIoeBc6wYcNi4sSJRcfe9773xciRIwvHr7vuupg7d26MGDEiKioq4qabbor6+vq45JJL+m5qAICj6PGLjI/lrrvuigEDBsTMmTOjs7MzGhsb49577+3rmwEAOKKSlFLq7yHerqOjIyorK6O9vd3rcQA45Y277aH+HqHHXlkwo8+v81R7/Pa3qACA7AgcACA7AgcAyI7AAQCyI3AAgOwIHAAgOwIHAMiOwAEAsiNwAIDsCBwAIDsCBwDIjsABALIjcACA7AgcACA7AgcAyI7AAQCyI3AAgOwIHAAgOwIHAMiOwAEAsiNwAIDsCBwAIDsCBwDIjsABALIjcACA7AgcACA7AgcAyI7AAQCyI3AAgOwIHAAgOwIHAMiOwAEAsiNwAIDsCBwAIDsCBwDIjsABALIjcACA7AgcACA7AgcAyI7AAQCyI3AAgOwIHAAgOwIHAMiOwAEAsiNwAIDsCBwAIDsCBwDIjsABALIjcACA7AgcACA7AgcAyI7AAQCyI3AAgOwIHAAgOwIHAMiOwAEAsiNwAIDsCBwAIDsCBwDIjsABALIjcACA7AgcACA7AgcAyI7AAQCyI3AAgOwIHAAgOwIHAMhOjwJn0aJFMWnSpKioqIiKioqor6+PRx55pHB+37590dTUFCNHjoyhQ4fGzJkzo62trc+HBgA4mh4FzhlnnBELFiyIlpaWWL9+fVx++eVx5ZVXxvPPPx8REbfccks8+OCDsWzZsli9enXs2LEjrr766hMyOADAkZSklFJvrmDEiBHx1a9+NT75yU/G6aefHvfff3988pOfjIiIn/70p3HuuefGmjVr4pJLLunW9XV0dERlZWW0t7dHRUVFb0YDgBNu3G0P9fcIPfbKghl9fp2n2uP3cb8G5+DBg7F06dLYu3dv1NfXR0tLSxw4cCAaGhoKayZMmBB1dXWxZs2aPhkWAKA7Snv6DRs3boz6+vrYt29fDB06NJYvXx7nnXdebNiwIcrKyqKqqqpofXV1dbS2th7x+jo7O6Ozs7PwdUdHR09HAgAo0uNncM4555zYsGFDrFu3Lm644YaYPXt2bN68+bgHaG5ujsrKysKltrb2uK8LACDiOAKnrKwszjrrrJgyZUo0NzfH5MmT42tf+1rU1NTE/v37Y9euXUXr29raoqam5ojXN2/evGhvby9ctm/f3uMfAgDg7Xr9OThdXV3R2dkZU6ZMiYEDB8aqVasK57Zs2RLbtm2L+vr6I35/eXl54W3nb10AAHqjR6/BmTdvXkyfPj3q6upi9+7dcf/998cTTzwRjz76aFRWVsZ1110Xc+fOjREjRkRFRUXcdNNNUV9f3+13UAEA9IUeBc7OnTvjT//0T+PVV1+NysrKmDRpUjz66KPx27/92xERcdddd8WAAQNi5syZ0dnZGY2NjXHvvfeekMEBAI6k15+D09dOtffRA8DR+BycN51qj9/+FhUAkB2BAwBkR+AAANkROABAdgQOAJAdgQMAZEfgAADZETgAQHYEDgCQHYEDAGRH4AAA2RE4AEB2BA4AkB2BAwBkR+AAANkROABAdgQOAJAdgQMAZEfgAADZETgAQHYEDgCQHYEDAGRH4AAA2RE4AEB2BA4AkB2BAwBkR+AAANkROABAdgQOAJAdgQMAZEfgAADZETgAQHYEDgCQHYEDAGRH4AAA2RE4AEB2BA4AkB2BAwBkR+AAANkROABAdgQOAJAdgQMAZEfgAADZETgAQHYEDgCQHYEDAGRH4AAA2RE4AEB2BA4AkB2BAwBkR+AAANkROABAdgQOAJAdgQMAZEfgAADZETgAQHYEDgCQHYEDAGRH4AAA2RE4AEB2BA4AkB2BAwBkR+AAANkROABAdgQOAJAdgQMAZEfgAADZETgAQHZ6FDjNzc3x4Q9/OIYNGxajR4+Oq666KrZs2VK0Zt++fdHU1BQjR46MoUOHxsyZM6Otra1PhwYAOJoeBc7q1aujqakp1q5dGytXrowDBw7Exz/+8di7d29hzS233BIPPvhgLFu2LFavXh07duyIq6++us8HBwA4ktKeLF6xYkXR10uWLInRo0dHS0tLfPSjH4329vb41re+Fffff39cfvnlERGxePHiOPfcc2Pt2rVxySWX9N3kAABH0KvX4LS3t0dExIgRIyIioqWlJQ4cOBANDQ2FNRMmTIi6urpYs2bNYa+js7MzOjo6ii4AAL1x3IHT1dUVc+bMiUsvvTQmTpwYERGtra1RVlYWVVVVRWurq6ujtbX1sNfT3NwclZWVhUttbe3xjgQAEBG9CJympqbYtGlTLF26tFcDzJs3L9rb2wuX7du39+r6AAB69Bqct9x4443xwx/+MJ588sk444wzCsdrampi//79sWvXrqJncdra2qKmpuaw11VeXh7l5eXHMwYAwGH16BmclFLceOONsXz58njsscdi/PjxReenTJkSAwcOjFWrVhWObdmyJbZt2xb19fV9MzEAwDH06BmcpqamuP/+++P73/9+DBs2rPC6msrKyhg8eHBUVlbGddddF3Pnzo0RI0ZERUVF3HTTTVFfX+8dVADASdOjwFm0aFFERHzsYx8rOr548eL49Kc/HRERd911VwwYMCBmzpwZnZ2d0djYGPfee2+fDAsA0B09CpyU0jHXDBo0KBYuXBgLFy487qEAAHrD36ICALIjcACA7AgcACA7AgcAyI7AAQCyI3AAgOwIHAAgOwIHAMiOwAEAsiNwAIDsCBwAIDsCBwDIjsABALIjcACA7AgcACA7AgcAyE5pfw9wso277aH+HuE94ZUFM/p7BADewzyDAwBkR+AAANkROABAdgQOAJAdgQMAZEfgAADZETgAQHYEDgCQHYEDAGRH4AAA2RE4AEB2BA4AkB2BAwBkR+AAANkROABAdgQOAJAdgQMAZEfgAADZETgAQHYEDgCQHYEDAGRH4AAA2RE4AEB2BA4AkB2BAwBkR+AAANkROABAdgQOAJAdgQMAZEfgAADZETgAQHYEDgCQHYEDAGRH4AAA2RE4AEB2BA4AkB2BAwBkR+AAANkROABAdgQOAJAdgQMAZEfgAADZETgAQHYEDgCQHYEDAGRH4AAA2RE4AEB2BA4AkB2BAwBkR+AAANnpceA8+eST8YlPfCLGjh0bJSUl8cADDxSdTynF7bffHmPGjInBgwdHQ0NDvPjii301LwDAMfU4cPbu3RuTJ0+OhQsXHvb8HXfcEffcc0/cd999sW7dunjf+94XjY2NsW/fvl4PCwDQHaU9/Ybp06fH9OnTD3supRR33313fPGLX4wrr7wyIiL+5V/+Jaqrq+OBBx6IP/qjP+rdtAAA3dCnr8HZunVrtLa2RkNDQ+FYZWVlTJs2LdasWXPY7+ns7IyOjo6iCwBAb/Rp4LS2tkZERHV1ddHx6urqwrl3am5ujsrKysKltra2L0cCAN6D+v1dVPPmzYv29vbCZfv27f09EgDwLtengVNTUxMREW1tbUXH29raCufeqby8PCoqKoouAAC90aeBM378+KipqYlVq1YVjnV0dMS6deuivr6+L28KAOCIevwuqj179sRLL71U+Hrr1q2xYcOGGDFiRNTV1cWcOXPib//2b+Pss8+O8ePHx5e+9KUYO3ZsXHXVVX05NwDAEfU4cNavXx+/9Vu/Vfh67ty5ERExe/bsWLJkSXzhC1+IvXv3xmc/+9nYtWtXXHbZZbFixYoYNGhQ300NAHAUPQ6cj33sY5FSOuL5kpKS+MpXvhJf+cpXejUYAMDx6vd3UQEA9DWBAwBkR+AAANkROABAdgQOAJAdgQMAZEfgAADZETgAQHYEDgCQHYEDAGRH4AAA2RE4AEB2BA4AkB2BAwBkR+AAANkROABAdgQOAJAdgQMAZEfgAADZETgAQHYEDgCQHYEDAGRH4AAA2RE4AEB2BA4AkB2BAwBkR+AAANkROABAdgQOAJAdgQMAZEfgAADZETgAQHYEDgCQHYEDAGRH4AAA2RE4AEB2BA4AkB2BAwBkR+AAANkROABAdgQOAJAdgQMAZEfgAADZETgAQHYEDgCQHYEDAGRH4AAA2RE4AEB2BA4AkB2BAwBkR+AAANkROABAdgQOAJAdgQMAZEfgAADZETgAQHZK+3sA8jTutof6e4Qee2XBjP4eAYA+4hkcACA7AgcAyI7AAQCyI3AAgOwIHAAgOwIHAMiOt4kDHMO78WMPInz0Ae9tnsEBALIjcACA7AgcACA7JyxwFi5cGOPGjYtBgwbFtGnT4qmnnjpRNwUAUOSEBM6//du/xdy5c2P+/PnxzDPPxOTJk6OxsTF27tx5Im4OAKDICQmcO++8Mz7zmc/EtddeG+edd17cd999MWTIkPj2t799Im4OAKBIn79NfP/+/dHS0hLz5s0rHBswYEA0NDTEmjVrDlnf2dkZnZ2dha/b29sjIqKjo6OvR4uIiK7OX5+Q6+Xd70Td53j3e7f+u+E+fXK8G+8fJ+K+8dZ1ppT6/LqPR58Hzi9/+cs4ePBgVFdXFx2vrq6On/70p4esb25uji9/+cuHHK+tre3r0eCoKu/u7wmgb7lPcyQn8r7xq1/9KiorK0/cDXRTv3/Q37x582Lu3LmFr7u6uuK1116LkSNHRklJSY+vr6OjI2pra2P79u1RUVHRl6O+J9i/3rF/vWP/esf+9Y7965329vaoq6uLESNG9PcoEXECAmfUqFFx2mmnRVtbW9Hxtra2qKmpOWR9eXl5lJeXFx2rqqrq9RwVFRXuoL1g/3rH/vWO/esd+9c79q93Bgw4NT6Bps+nKCsriylTpsSqVasKx7q6umLVqlVRX1/f1zcHAHCIE/Irqrlz58bs2bNj6tSpcfHFF8fdd98de/fujWuvvfZE3BwAQJETEjjXXHNN/OIXv4jbb789Wltb40Mf+lCsWLHikBcenwjl5eUxf/78Q37tRffYv96xf71j/3rH/vWO/eudU23/StKp8n4uAIA+cmq8EggAoA8JHAAgOwIHAMiOwAEAspNd4CxcuDDGjRsXgwYNimnTpsVTTz3V3yP1uSeffDI+8YlPxNixY6OkpCQeeOCBovMppbj99ttjzJgxMXjw4GhoaIgXX3yxaM1rr70Ws2bNioqKiqiqqorrrrsu9uzZU7Tmueeei4985CMxaNCgqK2tjTvuuOOQWZYtWxYTJkyIQYMGxQUXXBAPP/xwj2c5mZqbm+PDH/5wDBs2LEaPHh1XXXVVbNmypWjNvn37oqmpKUaOHBlDhw6NmTNnHvLBldu2bYsZM2bEkCFDYvTo0fH5z38+3njjjaI1TzzxRFx00UVRXl4eZ511VixZsuSQeY51f+3OLCfTokWLYtKkSYUPQquvr49HHnmkR/O+V/funRYsWBAlJSUxZ86cwjH7d3R/8zd/EyUlJUWXCRMmFM7bv6P7+c9/Hn/8x38cI0eOjMGDB8cFF1wQ69evL5zP7rEjZWTp0qWprKwsffvb307PP/98+sxnPpOqqqpSW1tbf4/Wpx5++OH013/91+k//uM/UkSk5cuXF51fsGBBqqysTA888ED6yU9+kn7v934vjR8/Pr3++uuFNb/zO7+TJk+enNauXZv+67/+K5111lnpU5/6VOF8e3t7qq6uTrNmzUqbNm1K3/3ud9PgwYPTN77xjcKaH//4x+m0005Ld9xxR9q8eXP64he/mAYOHJg2btzYo1lOpsbGxrR48eK0adOmtGHDhvS7v/u7qa6uLu3Zs6ew5vrrr0+1tbVp1apVaf369emSSy5Jv/Ebv1E4/8Ybb6SJEyemhoaG9Oyzz6aHH344jRo1Ks2bN6+w5uWXX05DhgxJc+fOTZs3b05f//rX02mnnZZWrFhRWNOd++uxZjnZfvCDH6SHHnoo/exnP0tbtmxJf/VXf5UGDhyYNm3a1K1538t793ZPPfVUGjduXJo0aVK6+eabC8ft39HNnz8/nX/++enVV18tXH7xi18Uztu/I3vttdfSmWeemT796U+ndevWpZdffjk9+uij6aWXXiqsye2xI6vAufjii1NTU1Ph64MHD6axY8em5ubmfpzqxHpn4HR1daWampr01a9+tXBs165dqby8PH33u99NKaW0efPmFBHp6aefLqx55JFHUklJSfr5z3+eUkrp3nvvTcOHD0+dnZ2FNbfeems655xzCl//4R/+YZoxY0bRPNOmTUt//ud/3u1Z+tvOnTtTRKTVq1enlN6cb+DAgWnZsmWFNS+88EKKiLRmzZqU0puBOWDAgNTa2lpYs2jRolRRUVHYry984Qvp/PPPL7qta665JjU2Nha+Ptb9tTuznAqGDx+e/umf/sneddPu3bvT2WefnVauXJl+8zd/sxA49u/Y5s+fnyZPnnzYc/bv6G699dZ02WWXHfF8jo8d2fyKav/+/dHS0hINDQ2FYwMGDIiGhoZYs2ZNP052cm3dujVaW1uL9qGysjKmTZtW2Ic1a9ZEVVVVTJ06tbCmoaEhBgwYEOvWrSus+ehHPxplZWWFNY2NjbFly5b4v//7v8Kat9/OW2veup3uzNLf2tvbIyIKfxyupaUlDhw4UDTzhAkToq6urmj/LrjggqIPrmxsbIyOjo54/vnnC2uOtjfdub92Z5b+dPDgwVi6dGns3bs36uvr7V03NTU1xYwZMw75Ge1f97z44osxduzY+MAHPhCzZs2Kbdu2RYT9O5Yf/OAHMXXq1PiDP/iDGD16dFx44YXxzW9+s3A+x8eObALnl7/8ZRw8ePCQT0uurq6O1tbWfprq5HvrZz3aPrS2tsbo0aOLzpeWlsaIESOK1hzuOt5+G0da8/bzx5qlP3V1dcWcOXPi0ksvjYkTJ0bEmzOXlZUd8gdf3/lzHe/edHR0xOuvv96t+2t3ZukPGzdujKFDh0Z5eXlcf/31sXz58jjvvPPsXTcsXbo0nnnmmWhubj7knP07tmnTpsWSJUtixYoVsWjRoti6dWt85CMfid27d9u/Y3j55Zdj0aJFcfbZZ8ejjz4aN9xwQ/zlX/5l/PM//3NE5PnYcUL+VAO8GzQ1NcWmTZviRz/6UX+P8q5yzjnnxIYNG6K9vT3+/d//PWbPnh2rV6/u77FOedu3b4+bb745Vq5cGYMGDervcd6Vpk+fXvjvSZMmxbRp0+LMM8+M733vezF48OB+nOzU19XVFVOnTo2///u/j4iICy+8MDZt2hT33XdfzJ49u5+nOzGyeQZn1KhRcdpppx3yKvW2traoqanpp6lOvrd+1qPtQ01NTezcubPo/BtvvBGvvfZa0ZrDXcfbb+NIa95+/liz9Jcbb7wxfvjDH8bjjz8eZ5xxRuF4TU1N7N+/P3bt2lW0/p0/1/HuTUVFRQwePLhb99fuzNIfysrK4qyzzoopU6ZEc3NzTJ48Ob72ta/Zu2NoaWmJnTt3xkUXXRSlpaVRWloaq1evjnvuuSdKS0ujurra/vVQVVVVfPCDH4yXXnrJ/e8YxowZE+edd17RsXPPPbfwK74cHzuyCZyysrKYMmVKrFq1qnCsq6srVq1aFfX19f042ck1fvz4qKmpKdqHjo6OWLduXWEf6uvrY9euXdHS0lJY89hjj0VXV1dMmzatsObJJ5+MAwcOFNasXLkyzjnnnBg+fHhhzdtv5601b91Od2Y52VJKceONN8by5cvjsccei/HjxxednzJlSgwcOLBo5i1btsS2bduK9m/jxo1F/6OvXLkyKioqCv+AHGtvunN/7c4sp4Kurq7o7Oy0d8dwxRVXxMaNG2PDhg2Fy9SpU2PWrFmF/7Z/PbNnz574n//5nxgzZoz73zFceumlh3wkxs9+9rM488wzIyLTx45uvxz5XWDp0qWpvLw8LVmyJG3evDl99rOfTVVVVUWvmM/B7t2707PPPpueffbZFBHpzjvvTM8++2z63//935TSm2+vq6qqSt///vfTc889l6688srDvtXvwgsvTOvWrUs/+tGP0tlnn130Vr9du3al6urq9Cd/8idp06ZNaenSpWnIkCGHvNWvtLQ0/cM//EN64YUX0vz58w/7Vr9jzXIy3XDDDamysjI98cQTRW81/fWvf11Yc/3116e6urr02GOPpfXr16f6+vpUX19fOP/WW00//vGPpw0bNqQVK1ak008//bBvNf385z+fXnjhhbRw4cLDvtX0WPfXY81yst12221p9erVaevWrem5555Lt912WyopKUn/+Z//2a1538t7dzhvfxdVSvbvWD73uc+lJ554Im3dujX9+Mc/Tg0NDWnUqFFp586d3Zr5vbx/Tz31VCotLU1/93d/l1588cX0ne98Jw0ZMiT967/+a2FNbo8dWQVOSil9/etfT3V1damsrCxdfPHFae3atf09Up97/PHHU0Qccpk9e3ZK6c232H3pS19K1dXVqby8PF1xxRVpy5YtRdfxq1/9Kn3qU59KQ4cOTRUVFenaa69Nu3fvLlrzk5/8JF122WWpvLw8vf/9708LFiw4ZJbvfe976YMf/GAqKytL559/fnrooYeKzndnlpPpcPsWEWnx4sWFNa+//nr6i7/4izR8+PA0ZMiQ9Pu///vp1VdfLbqeV155JU2fPj0NHjw4jRo1Kn3uc59LBw4cKFrz+OOPpw996EOprKwsfeADHyi6jbcc6/7anVlOpj/7sz9LZ555ZiorK0unn356uuKKKwpx091536t7dzjvDBz7d3TXXHNNGjNmTCorK0vvf//70zXXXFP0OS727+gefPDBNHHixFReXp4mTJiQ/vEf/7HofG6PHSUppdT953sAAE592bwGBwDgLQIHAMiOwAEAsiNwAIDsCBwAIDsCBwDIjsABALIjcACA7AgcACA7AgcAyI7AAQCyI3AAgOz8P01HDmPDzByBAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist([unitPop[homeU[t]] for t in stillOver])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "id": "3e80ff56-7d63-4aca-b84a-bae0cdc3d835",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "here are centerpoints of overpopped HDs\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"here are centerpoints of overpopped HDs\")\n",
    "for t in stillOver:\n",
    "    plotPoly(HDCP[t].buffer(0.02),1)\n",
    "for c in range(nCounties):\n",
    "    plotPoly(countyGeom[c])\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] > 1.2 :\n",
    "        plotPoly(unitGeom[u],0.5)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "id": "2bf4579a-03ec-43b0-9864-4aaafd3c8119",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "number of units in overpopped HDs by home muni pop\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "nMunisInOverPs = [len(HDunitList[t]) for t in stillOver]\n",
    "plt.scatter([unitPop[homeU[t]] for t in stillOver],nMunisInOverPs)\n",
    "print(\"number of units in overpopped HDs by home muni pop\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "id": "dc736ef8-0f54-4330-918c-e287db517f59",
   "metadata": {},
   "outputs": [],
   "source": [
    "for t in popHDlist:\n",
    "    if homeU[t] not in HDunitList[t]:\n",
    "        print(homeU[t],\"unit is not in HD\",t)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "348895e0-eef9-4b4d-a085-85a15daa824a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "preparing to add some splits if we choose to do so\n"
     ]
    }
   ],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "id": "05a09abc-159f-4602-a43c-c7554919dc74",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "since we have a lot of stillOver HDs, lets rebuild from scratch so these can be in play for later patching\n"
     ]
    }
   ],
   "source": [
    "print(\"since we have a lot of stillOver HDs, lets rebuild from scratch so these can be in play for later patching\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "id": "45f21736-2e5c-4bc9-b7d3-66e6f3d070f7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "now working on the 82 overpopped units.  Try building from home muni, adding any nearby whole units\n",
      "working on alt unit list for HD 22\n",
      "working on alt unit list for HD 298\n",
      "working on alt unit list for HD 381\n",
      "working on alt unit list for HD 506\n",
      "working on alt unit list for HD 2390\n",
      "working on alt unit list for HD 2437\n",
      "working on alt unit list for HD 7122\n",
      "working on alt unit list for HD 7592\n",
      "working on alt unit list for HD 8926\n",
      "all done attempting 82 stillOvers.  We got stuck on 0\n"
     ]
    }
   ],
   "source": [
    "stillNotRight = list()\n",
    "print(\"now working on the\",len(stillOver),\"overpopped units.  Try building from home muni, adding any nearby whole units\")\n",
    "\n",
    "for i, t in enumerate(stillOver):\n",
    "    if i%10 == 0:\n",
    "        print(\"working on alt unit list for HD\",t)\n",
    "    HDunitList[t] = [homeU[t] ]\n",
    "    currPop = unitPop[homeU[t]]\n",
    "    currSet = {homeU[t] }\n",
    "    unbroken, noEnclave,smallPieceList,enclaveList = enclaveCheck(list(currSet) , unitNbrs,4)\n",
    "    if unbroken and not noEnclave: #the original home unit surrounds some small units; need to fill in first\n",
    "        enclavePop = np.sum([unitPop[u] for u in enclaveList])\n",
    "        if currPop + enclavePop < maxDistrictPop:  #we can fill the enclave\n",
    "            currPop += enclavePop\n",
    "            HDunitList[t] += enclaveList\n",
    "            currSet = currSet.union(set(enclaveList))\n",
    "        else:\n",
    "            print(\"HD\",t,\"is a nonstarter because the home unit encloses a large enclave\")\n",
    "            stillNotRight.append(t)\n",
    "    eligSet = set(unitNbrs[homeU[t]] ) #a seed to satisfy below while loop\n",
    "    for u in currSet:\n",
    "        eligSet = eligSet.union(set(unitNbrs[u]))  #in case we just filled an enclave above\n",
    "    eligList = list( eligSet.difference(currSet) )\n",
    "    while currPop < minDistrictPop and len(eligList) > 0:\n",
    "        eligSet = set(unitNbrs[homeU[t]]).difference(currSet)\n",
    "        for uu in currSet:\n",
    "            for uuu in unitNbrs[uu]:\n",
    "                if uuu not in currSet:\n",
    "                    eligSet.add(uuu)\n",
    "        DQset = set()  #units we disqualify for being too big or would trigger an enclave if added\n",
    "        for u in eligSet:\n",
    "            if unitPop[u] > maxDistrictPop - currPop:\n",
    "                DQset.add(u)\n",
    "        for u in eligSet.difference(DQset):\n",
    "            unbroken, noEnclave,smallPieceList,enclaveList = enclaveCheck(list(currSet) + [u], unitNbrs,4)\n",
    "            if not (unbroken and noEnclave):  #would adding this unit create an enclave?\n",
    "                DQset.add(u)\n",
    "        eligList = list(eligSet.difference(DQset))\n",
    "        eligDist = [HDCP[t].distance(unitCP[u]) for u in eligList ]\n",
    "        if len(eligList) > 0:\n",
    "            eligU = eligList[eligDist.index(np.min(eligDist)) ]\n",
    "            currPop += unitPop[eligU]\n",
    "            HDunitList[t].append(eligU)\n",
    "            currSet.add(eligU)\n",
    "            #print(\"adding unit\",eligU,\"currPop now\",currPop)\n",
    "        else:\n",
    "            print(\"STUCK rebuilding from scratch for HD\",t,\"final pop/aDP =\",currPop/aDP )\n",
    "            stillNotRight.append(t)\n",
    "        \n",
    "    HDvPop[t] = np.sum([unitPop[u] for u in HDunitList[t] ])\n",
    "print(\"all done attempting\",len(stillOver),\"stillOvers.  We got stuck on\",len(stillNotRight) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "id": "ee7afc35-219a-4458-8d1f-6d5bffadc39d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "update classification of HDs by contiguity\n",
      "quick classification: who has contiguity problems?\n",
      "working on HD 0 time is now 0\n",
      "working on HD 700 time is now 4\n",
      "working on HD 1402 time is now 6\n",
      "working on HD 2102 time is now 9\n",
      "working on HD 2802 time is now 15\n",
      "working on HD 3503 time is now 18\n",
      "working on HD 4204 time is now 21\n",
      "working on HD 4906 time is now 24\n",
      "working on HD 5606 time is now 28\n",
      "working on HD 6306 time is now 32\n",
      "working on HD 7006 time is now 36\n",
      "working on HD 7706 time is now 38\n",
      "working on HD 8407 time is now 43\n",
      "out of 8934 total HDs, there were 8934.0 contiguous and 8934.0 complement-contiguous HDs\n",
      "0 HDs had both discontiguity problems, while enclave-only = 0 and discontig only= 0\n"
     ]
    }
   ],
   "source": [
    "print(\"update classification of HDs by contiguity\") #take from vanillaHD\n",
    "\n",
    "### THIS IS THE \"FIND DISCO\" CODE\n",
    "print(\"quick classification: who has contiguity problems?\")\n",
    "nUnbroken, nNoEnclave, smallPieceLists, enclaveLists, sPgenerator, eLgenerator = 0., 0., list(), list(), list(), list()\n",
    "smallPieceLengths, enclaveLengths = list(), list()\n",
    "doubleTroubleList = list()\n",
    "startTime = time.time()\n",
    "for i,t in enumerate(popHDlist):\n",
    "    if i%700 == 0:\n",
    "        print(\"working on HD\",t,\"time is now\",int(time.time() - startTime) )\n",
    "    unbroken, noEnclave,smallPieceList,enclaveList = enclaveCheck(HDunitList[t], unitNbrs,4) #,6) #6 is high (slow) to try to avoid false enclaves\n",
    "    if unbroken:\n",
    "        nUnbroken +=1\n",
    "    if noEnclave:\n",
    "        nNoEnclave +=1\n",
    "    if not unbroken:\n",
    "        smallPieceLists.append(smallPieceList)\n",
    "        smallPieceLengths.append(len(smallPieceList))\n",
    "        sPgenerator.append(t)\n",
    "    if not noEnclave and unbroken:   #district is contiguous but contains 1+ enclave\n",
    "        enclaveLists.append(enclaveList)\n",
    "        enclaveLengths.append(len(enclaveList))\n",
    "        eLgenerator.append(t)\n",
    "    if not noEnclave and not unbroken:  #extremely discontig (\"broken\") HDs can appear to have enclaves;\n",
    "        doubleTroubleList.append(t)\n",
    "print(\"out of\",len(popHDlist),\"total HDs, there were\",nUnbroken,\"contiguous and\",nNoEnclave,\"complement-contiguous HDs\")\n",
    "print(len(doubleTroubleList),\"HDs had both discontiguity problems, while enclave-only =\",len(eLgenerator),\n",
    "      \"and discontig only=\",len(sPgenerator)-len(doubleTroubleList) )\n",
    "\n",
    "if len(smallPieceLists) + len(enclaveLists) > 0:\n",
    "    print(\"here are the histograms of the small piece and enclave list lengths, total no =\",\n",
    "          len(smallPieceLists),len(enclaveLists) )\n",
    "    plt.hist([s for s in smallPieceLengths],label=\"small piece l units\",histtype='step',\n",
    "             cumulative=True,bins=[0,1,2,3,4,5,6,8,10,12,15,20,25,30,35,40,45,50,60,80,120,200])\n",
    "    plt.hist([e for e in enclaveLengths],label=\"enclave l units\",histtype='step',\n",
    "             cumulative=True,bins=[0,1,2,3,4,5,6,8,10,12,15,20,25,30,35,40,45,50,60,80,120,200])\n",
    "    plt.legend()\n",
    "    plt.show()\n",
    "    print(\"And here are the small-HD-piece and small-enclave pops\")\n",
    "    plt.hist([sum(unitPop[u] for u in s) for s in smallPieceLists],label=\"small piece 1 pop\",histtype='step')\n",
    "    plt.hist([sum(unitPop[u] for u in e) for e in enclaveLists],label=\"enclave 1 pop\",histtype='step')\n",
    "    plt.legend()\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "id": "5cb421b9-5843-4d26-8f38-5bbbc4b0f16f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "OK, looking good.  Update the HDvPops to reflect the partials, check contiguity one last time\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "current avg use and its sd are 1.00017 0.11109\n"
     ]
    },
    {
     "data": {
      "image/png": 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Hw5o0aZI++uijNo/x+Xxyu92RzePxdHZMAABwmnNYlmV15sCf//zneumll/Taa69p8ODBHT7u+PHjGjlypGbNmqUHHnig1TWhUEihUCjydTAYlMfjUSAQkMvl6sy4QK8xtHiT6RF6hQOL80yPAJz2gsGg3G73SV+/bd0z8q358+dr48aN2r59u60QkaQzzjhD48aN0759+9pc43Q65XQ6OzMaAACIMbZ+TWNZlubPn69169bplVde0bBhw2w/YEtLi3bv3q20tDTbxwIAgPhj68pIYWGhysvLtWHDBiUlJcnv90uS3G63+vfvL0kqKChQenq6fD6fJOn+++/XxIkTNXz4cB05ckQPP/ywDh48qLlz53bxUwEAALHIVowsX75cknT11VdH7V+9erV++tOfSpLq6+vVp893F1y++OIL3XrrrfL7/RowYICysrK0Y8cOjRo16tQmBwAAcaHTN7D2pI7eAAOAG1h7CjewAifX0ddvPpsGAAAYRYwAAACjiBEAAGAUMQIAAIwiRgAAgFHECAAAMIoYAQAARhEjAADAKGIEAAAYRYwAAACjiBEAAGAUMQIAAIwiRgAAgFHECAAAMIoYAQAARhEjAADAKGIEAAAYRYwAAACjiBEAAGAUMQIAAIwiRgAAgFHECAAAMIoYAQAARhEjAADAKGIEAAAYRYwAAACjiBEAAGAUMQIAAIwiRgAAgFHECAAAMIoYAQAARhEjAADAKFsx4vP5dOWVVyopKUnJycnKz8/X3r17T3rc2rVrdemllyoxMVFjxozR5s2bOz0wAACIL7Zi5NVXX1VhYaHeeOMNVVZW6vjx47ruuuvU3Nzc5jE7duzQrFmzNGfOHNXW1io/P1/5+fnas2fPKQ8PAABin8OyLKuzB3/66adKTk7Wq6++qu9///utrpk5c6aam5u1cePGyL6JEycqMzNTK1as6NDjBINBud1uBQIBuVyuzo4L9ApDizeZHqFXOLA4z/QIwGmvo6/fp3TPSCAQkCQNHDiwzTXV1dXKycmJ2pebm6vq6uo2jwmFQgoGg1EbAACIT52OkXA4rIULF2ry5MkaPXp0m+v8fr9SUlKi9qWkpMjv97d5jM/nk9vtjmwej6ezYwIAgNNcp2OksLBQe/bsUUVFRVfOI0kqKSlRIBCIbIcOHeryxwAAAKeHhM4cNH/+fG3cuFHbt2/X4MGD212bmpqqxsbGqH2NjY1KTU1t8xin0ymn09mZ0QAAQIyxdWXEsizNnz9f69at0yuvvKJhw4ad9Biv16uqqqqofZWVlfJ6vfYmBQAAccnWlZHCwkKVl5drw4YNSkpKitz34Xa71b9/f0lSQUGB0tPT5fP5JEkLFixQdna2lixZory8PFVUVGjnzp1auXJlFz8VAAAQi2xdGVm+fLkCgYCuvvpqpaWlRbY1a9ZE1tTX16uhoSHy9aRJk1ReXq6VK1cqIyNDzz//vNavX9/uTa8AAKD3sHVlpCNvSbJt27YT9l1//fW6/vrr7TwUAADoJfhsGgAAYBQxAgAAjCJGAACAUcQIAAAwihgBAABGESMAAMAoYgQAABhFjAAAAKOIEQAAYBQxAgAAjCJGAACAUcQIAAAwihgBAABGESMAAMAoYgQAABhFjAAAAKOIEQAAYBQxAgAAjCJGAACAUcQIAAAwihgBAABGESMAAMAoYgQAABhFjAAAAKOIEQAAYBQxAgAAjCJGAACAUcQIAAAwKsH0AAAQi4YWbzI9gm0HFueZHgFoFVdGAACAUcQIAAAwynaMbN++XdOnT9egQYPkcDi0fv36dtdv27ZNDofjhM3v93d2ZgAAEEdsx0hzc7MyMjK0bNkyW8ft3btXDQ0NkS05OdnuQwMAgDhk+wbWadOmadq0abYfKDk5Weecc47t4wAAQHzrsXtGMjMzlZaWpqlTp+r1119vd20oFFIwGIzaAABAfOr2GElLS9OKFSv0wgsv6IUXXpDH49HVV1+tXbt2tXmMz+eT2+2ObB6Pp7vHBAAAhjgsy7I6fbDDoXXr1ik/P9/WcdnZ2RoyZIj+8pe/tPr9UCikUCgU+ToYDMrj8SgQCMjlcnV2XKBXiMX3v0DP4H1G0NOCwaDcbvdJX7+NvOnZ+PHj9dprr7X5fafTKafT2YMTAQAAU4y8z0hdXZ3S0tJMPDQAADjN2L4y0tTUpH379kW+/vDDD1VXV6eBAwdqyJAhKikp0ccff6ynn35akrR06VINGzZMl112mb766is99dRTeuWVV7R169auexYAACBm2Y6RnTt3asqUKZGvi4qKJEmzZ89WWVmZGhoaVF9fH/n+sWPH9Mtf/lIff/yxzjzzTI0dO1b/+Mc/on4GAADovU7pBtae0tEbYABwAyvaxg2s6Gkdff3ms2kAAIBRxAgAADCKGAEAAEYRIwAAwChiBAAAGEWMAAAAo4gRAABgFDECAACMIkYAAIBRxAgAADCKGAEAAEYRIwAAwChiBAAAGEWMAAAAo4gRAABgFDECAACMIkYAAIBRxAgAADCKGAEAAEYRIwAAwChiBAAAGEWMAAAAo4gRAABgFDECAACMIkYAAIBRxAgAADCKGAEAAEYRIwAAwChiBAAAGEWMAAAAo4gRAABgFDECAACMsh0j27dv1/Tp0zVo0CA5HA6tX7/+pMds27ZNl19+uZxOp4YPH66ysrJOjAoAAOKR7Rhpbm5WRkaGli1b1qH1H374ofLy8jRlyhTV1dVp4cKFmjt3rrZs2WJ7WAAAEH8S7B4wbdo0TZs2rcPrV6xYoWHDhmnJkiWSpJEjR+q1117T73//e+Xm5tp9eAAAEGdsx4hd1dXVysnJidqXm5urhQsXtnlMKBRSKBSKfB0MBrtrPKBdQ4s3mR4BAOJet9/A6vf7lZKSErUvJSVFwWBQX375ZavH+Hw+ud3uyObxeLp7TAAAYMhp+dc0JSUlCgQCke3QoUOmRwIAAN2k239Nk5qaqsbGxqh9jY2Ncrlc6t+/f6vHOJ1OOZ3O7h4NAACcBrr9yojX61VVVVXUvsrKSnm93u5+aAAAEANsx0hTU5Pq6upUV1cn6Zs/3a2rq1N9fb2kb37FUlBQEFk/b9487d+/X3fddZfee+89PfHEE3ruued0xx13dM0zAAAAMc12jOzcuVPjxo3TuHHjJElFRUUaN26c7rvvPklSQ0NDJEwkadiwYdq0aZMqKyuVkZGhJUuW6KmnnuLPegEAgCTJYVmWZXqIkwkGg3K73QoEAnK5XKbHQS/Cn/YinhxYnGd6BPQyHX39Pi3/mgYAAPQexAgAADCKGAEAAEYRIwAAwChiBAAAGEWMAAAAo4gRAABgFDECAACMIkYAAIBRxAgAADCKGAEAAEYRIwAAwChiBAAAGEWMAAAAo4gRAABgFDECAACMIkYAAIBRxAgAADCKGAEAAEYlmB4AANAzhhZvMj2CbQcW55keAT2AKyMAAMAoYgQAABhFjAAAAKOIEQAAYBQxAgAAjCJGAACAUcQIAAAwihgBAABGESMAAMAoYgQAABhFjAAAAKM6FSPLli3T0KFDlZiYqAkTJujNN99sc21ZWZkcDkfUlpiY2OmBAQBAfLEdI2vWrFFRUZFKS0u1a9cuZWRkKDc3V4cPH27zGJfLpYaGhsh28ODBUxoaAADED9sx8uijj+rWW2/VLbfcolGjRmnFihU688wztWrVqjaPcTgcSk1NjWwpKSmnNDQAAIgftmLk2LFjqqmpUU5Oznc/oE8f5eTkqLq6us3jmpqadMEFF8jj8WjGjBl6++23232cUCikYDAYtQEAgPhkK0Y+++wztbS0nHBlIyUlRX6/v9VjRowYoVWrVmnDhg165plnFA6HNWnSJH300UdtPo7P55Pb7Y5sHo/HzpgAACCGdPtf03i9XhUUFCgzM1PZ2dl68cUXdf755+vJJ59s85iSkhIFAoHIdujQoe4eEwAAGJJgZ/F5552nvn37qrGxMWp/Y2OjUlNTO/QzzjjjDI0bN0779u1rc43T6ZTT6bQzGgAAiFG2roz069dPWVlZqqqqiuwLh8OqqqqS1+vt0M9oaWnR7t27lZaWZm9SAAAQl2xdGZGkoqIizZ49W1dccYXGjx+vpUuXqrm5WbfccoskqaCgQOnp6fL5fJKk+++/XxMnTtTw4cN15MgRPfzwwzp48KDmzp3btc8EAADEJNsxMnPmTH366ae677775Pf7lZmZqZdffjlyU2t9fb369PnugssXX3yhW2+9VX6/XwMGDFBWVpZ27NihUaNGdd2zAAAAMcthWZZleoiTCQaDcrvdCgQCcrlcpsdBLzK0eJPpEYBe7cDiPNMj4BR09PWbz6YBAABGESMAAMAoYgQAABhFjAAAAKOIEQAAYBQxAgAAjCJGAACAUcQIAAAwihgBAABGESMAAMAoYgQAABhFjAAAAKOIEQAAYFSC6QEAAGhLLH5yNp80bB9XRgAAgFHECAAAMIoYAQAARhEjAADAKGIEAAAYRYwAAACj+NNe9IhY/PM8AEDP4MoIAAAwihgBAABGESMAAMAoYgQAABhFjAAAAKOIEQAAYBQxAgAAjCJGAACAUcQIAAAwindgBQCgC8XiO04fWJxn9PE7dWVk2bJlGjp0qBITEzVhwgS9+eab7a5fu3atLr30UiUmJmrMmDHavHlzp4YFAADxx3aMrFmzRkVFRSotLdWuXbuUkZGh3NxcHT58uNX1O3bs0KxZszRnzhzV1tYqPz9f+fn52rNnzykPDwAAYp/DsizLzgETJkzQlVdeqccff1ySFA6H5fF4dPvtt6u4uPiE9TNnzlRzc7M2btwY2Tdx4kRlZmZqxYoVHXrMYDAot9utQCAgl8tlZ1ycJmLxsiUA9Bbd9Wuajr5+27pn5NixY6qpqVFJSUlkX58+fZSTk6Pq6upWj6murlZRUVHUvtzcXK1fv77NxwmFQgqFQpGvA4GApG+eFKTRpVtMjwAAiCPd9fr67c892XUPWzHy2WefqaWlRSkpKVH7U1JS9N5777V6jN/vb3W93+9v83F8Pp8WLVp0wn6Px2NnXAAA0AHupd37848ePSq3293m90/Lv6YpKSmJupoSDof1+eef69xzz5XD4TA42ekpGAzK4/Ho0KFD/Bqrh3HuzeHcm8X5NyeWzr1lWTp69KgGDRrU7jpbMXLeeeepb9++amxsjNrf2Nio1NTUVo9JTU21tV6SnE6nnE5n1L5zzjnHzqi9ksvlOu3/w4xXnHtzOPdmcf7NiZVz394VkW/Z+muafv36KSsrS1VVVZF94XBYVVVV8nq9rR7j9Xqj1ktSZWVlm+sBAEDvYvvXNEVFRZo9e7auuOIKjR8/XkuXLlVzc7NuueUWSVJBQYHS09Pl8/kkSQsWLFB2draWLFmivLw8VVRUaOfOnVq5cmXXPhMAABCTbMfIzJkz9emnn+q+++6T3+9XZmamXn755chNqvX19erT57sLLpMmTVJ5ebnuvfde3X333br44ou1fv16jR49uuueRS/ndDpVWlp6wq+20P049+Zw7s3i/JsTj+fe9vuMAAAAdCU+KA8AABhFjAAAAKOIEQAAYBQxAgAAjCJGYsSyZcs0dOhQJSYmasKECXrzzTfbXX/kyBEVFhYqLS1NTqdTl1xyiTZv3txD08YXu+d+6dKlGjFihPr37y+Px6M77rhDX331VQ9NGz+2b9+u6dOna9CgQXI4HO1+ntW3tm3bpssvv1xOp1PDhw9XWVlZt88Zj+ye+xdffFFTp07V+eefL5fLJa/Xqy1b+AytzujMf/ffev3115WQkKDMzMxum6+7ECMxYM2aNSoqKlJpaal27dqljIwM5ebm6vDhw62uP3bsmKZOnaoDBw7o+eef1969e/XHP/5R6enpPTx57LN77svLy1VcXKzS0lK9++67+tOf/qQ1a9bo7rvv7uHJY19zc7MyMjK0bNmyDq3/8MMPlZeXpylTpqiurk4LFy7U3LlzeVHsBLvnfvv27Zo6dao2b96smpoaTZkyRdOnT1dtbW03Txp/7J77bx05ckQFBQW69tpru2mybmbhtDd+/HirsLAw8nVLS4s1aNAgy+fztbp++fLl1oUXXmgdO3asp0aMW3bPfWFhoXXNNddE7SsqKrImT57crXPGO0nWunXr2l1z1113WZdddlnUvpkzZ1q5ubndOFn868i5b82oUaOsRYsWdf1AvYidcz9z5kzr3nvvtUpLS62MjIxunas7cGXkNHfs2DHV1NQoJycnsq9Pnz7KyclRdXV1q8f87W9/k9frVWFhoVJSUjR69Gj99re/VUtLS0+NHRc6c+4nTZqkmpqayK9y9u/fr82bN+uHP/xhj8zcm1VXV0f9W0lSbm5um/9W6D7hcFhHjx7VwIEDTY/SK6xevVr79+9XaWmp6VE67bT81F5857PPPlNLS0vkHW6/lZKSovfee6/VY/bv369XXnlFN910kzZv3qx9+/bpF7/4hY4fPx7T/7H2tM6c+xtvvFGfffaZrrrqKlmWpa+//lrz5s3j1zQ9wO/3t/pvFQwG9eWXX6p///6GJut9HnnkETU1NemGG24wPUrc++CDD1RcXKx//etfSkiI3Zd0rozEoXA4rOTkZK1cuVJZWVmaOXOm7rnnHq1YscL0aHFv27Zt+u1vf6snnnhCu3bt0osvvqhNmzbpgQceMD0a0CPKy8u1aNEiPffcc0pOTjY9TlxraWnRjTfeqEWLFumSSy4xPc4pid2M6iXOO+889e3bV42NjVH7GxsblZqa2uoxaWlpOuOMM9S3b9/IvpEjR8rv9+vYsWPq169ft84cLzpz7n/961/r5ptv1ty5cyVJY8aMUXNzs2677Tbdc889UZ/bhK6Vmpra6r+Vy+XiqkgPqaio0Ny5c7V27doTfmWGrnf06FHt3LlTtbW1mj9/vqRv/s+oZVlKSEjQ1q1bdc011xiesmP4X8bTXL9+/ZSVlaWqqqrIvnA4rKqqKnm93laPmTx5svbt26dwOBzZ9/777ystLY0QsaEz5/5///vfCcHxbRRafAxUt/J6vVH/VpJUWVnZ5r8Vutazzz6rW265Rc8++6zy8vJMj9MruFwu7d69W3V1dZFt3rx5GjFihOrq6jRhwgTTI3ac4Rto0QEVFRWW0+m0ysrKrHfeece67bbbrHPOOcfy+/2WZVnWzTffbBUXF0fW19fXW0lJSdb8+fOtvXv3Whs3brSSk5OtBx980NRTiFl2z31paamVlJRkPfvss9b+/futrVu3WhdddJF1ww03mHoKMevo0aNWbW2tVVtba0myHn30Uau2ttY6ePCgZVmWVVxcbN18882R9fv377fOPPNM684777Teffdda9myZVbfvn2tl19+2dRTiFl2z/1f//pXKyEhwVq2bJnV0NAQ2Y4cOWLqKcQsu+f+/xerf01DjMSIP/zhD9aQIUOsfv36WePHj7feeOONyPeys7Ot2bNnR63fsWOHNWHCBMvpdFoXXnih9dBDD1lff/11D08dH+yc++PHj1u/+c1vrIsuushKTEy0PB6P9Ytf/ML64osven7wGPfPf/7TknTC9u35nj17tpWdnX3CMZmZmVa/fv2sCy+80Fq9enWPzx0P7J777Ozsdtej4zrz3/3/Fasx4rAsrh0DAABzuGcEAAAYRYwAAACjiBEAAGAUMQIAAIwiRgAAgFHECAAAMIoYAQAARhEjAADAKGIEAAAYRYwAAACjiBEAAGAUMQIAAIz6f9iQPV39p01NAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"OK, looking good.  Update the HDvPops to reflect the partials, check contiguity one last time\")\n",
    "HDvPop = [0.]*nHDs\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        HDvPop[t] += unitPop[u]\n",
    "\n",
    "plt.hist([HDvPop[t] for t in popHDlist])\n",
    "plt.axvline(aDP,ls=\"--\")\n",
    "plt.axvline(0.995*aDP,ls=\"dotted\")\n",
    "plt.axvline(1.005*aDP,ls=\"dotted\")\n",
    "plt.show()\n",
    "unitUse = [0.]*nUnits\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += HDweight[t] * nDistricts\n",
    "\n",
    "currAvg, currSD = getWeightedAvgAndSD(unitUse, unitPop)\n",
    "print(\"current avg use and its sd are\",r5(currAvg),r5(currSD) )\n",
    "plt.hist(unitUse,weights=unitPop)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "id": "aecf5e44-30a1-4fe0-9eba-6e0545947ef7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "preparing to add some splits if we choose to do so\n"
     ]
    }
   ],
   "source": [
    "print(\"preparing to add some splits if we choose to do so\")\n",
    "splitUnitNo, splitUnitFrac, hasSplitUnit = [-999]*nHDs, [0.]*nHDs, [0]*nHDs \n",
    "splitPops  = [0]*nHDs\n",
    "nSplittables = list()\n",
    "afterSplitHDvPop = HDvPop.copy()"
   ]
  },
  {
   "cell_type": "raw",
   "id": "9cd95826-0f53-456f-bf27-f1010fb6f18a",
   "metadata": {},
   "source": [
    "unsplittableUnits = list()  #redo this preliminary if we had a cold restart\n",
    "for u in range(nUnits):\n",
    "    if unitPop[u] > 0.5 * aDP and unitPop[u] < 1.05 * aDP:\n",
    "        unsplittableUnits.append(u)\n",
    "        \n",
    "mustSplit = stillStillUnder + stillNotRight\n",
    "print(\"we will now add split units to these\",len(mustSplit),\"HDs that are just under\")\n",
    "print(\"Most of these appear to be legit blocky areas\")\n",
    "print(\"We will therefore add a partial to meet aDP.  We will avoid adding partials that could potentially create an enclave\")\n",
    "PLOT = False\n",
    "for t in mustSplit:\n",
    "    splittableSet = set()\n",
    "    for u in HDunitList[t]:\n",
    "        for uu in unitNbrs[u]:\n",
    "            splittableSet = splittableSet.union(set(unitNbrs[u]) )\n",
    "    splittableSet = (splittableSet.difference(set(HDunitList[t])) ).difference(set(unsplittableUnits))\n",
    "    for u in splittableSet.copy():\n",
    "        unbroken, noEnclave,smallPieceList,enclaveList = enclaveCheck(HDunitList[t] + [u], unitNbrs,4)\n",
    "        if not (unbroken and noEnclave):\n",
    "            splittableSet.remove(u)\n",
    "    splittables = list(splittableSet)\n",
    "    if len(splittables) == 0:\n",
    "        print(\"cannot conventionally add a splittable unit to HD\",t,\"; there are none nearby\")\n",
    "    else:\n",
    "        splitDist = [unitGeom[u].distance(HDCP[t]) for u in splittables]\n",
    "        splitU = splittables[splitDist.index(np.min(splitDist))]\n",
    "        hasSplitUnit[t] = 1\n",
    "        splitUnitNo[t] = splitU\n",
    "        addedPop = 0.5*(aDP + minDistrictPop) - HDvPop[t]  #waffle between min splitting and target pop for this HD\n",
    "        #HDunitList[t].append(splitU)  #not yet -- see a below block\n",
    "        splitUnitFrac[t] = addedPop / unitPop[splitU]\n",
    "        afterSplitHDvPop[t] += addedPop\n",
    "print(\"done with\",len(mustSplit),\"mustSplit HDs\")"
   ]
  },
  {
   "cell_type": "raw",
   "id": "2e816d93-61c1-479e-9ec8-225194f4e512",
   "metadata": {},
   "source": [
    "plt.scatter([HDvPop[t] for t in mustSplit],[afterSplitHDvPop[t] for t in mustSplit])\n",
    "print(\"adjusted vs original pop for splitters\")\n",
    "plt.axhline(minDistrictPop,ls = \"--\")\n",
    "plt.axhline(maxDistrictPop,ls = \"--\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "1ee7c8e4-cb8f-4cec-97ca-cf36c605fe52",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "OK, looking good.  Update the HDvPops to reflect the partials, check contiguity one last time\n"
     ]
    }
   ],
   "source": [
    "print(\"OK, looking good.  Update the HDvPops to reflect the partials, check contiguity one last time\")\n",
    "HDvPop = [0.]*nHDs\n",
    "for t in popHDlist:\n",
    "    if t%1000 == 0:\n",
    "        print(\"final check on HD\",t)\n",
    "    for u in HDunitList[t]:\n",
    "        HDvPop[t] += unitPop[u]\n",
    "    if splitUnitNo[t] >= 0:\n",
    "        u = splitUnitNo[t]\n",
    "        if u in HDunitList[t]:  #we had added the full unit pop (shouldn't have happened)\n",
    "            HDvPop[t] -= (1. - splitUnitFrac[t]) * unitPop[u]\n",
    "        else:\n",
    "            HDvPop[t] += splitUnitFrac[t] * unitPop[u]\n",
    "            HDunitList[t].append(splitUnitNo[t])\n",
    "    \n",
    "    unbroken, noEnclave,smallPieceList,enclaveList = enclaveCheck(HDunitList[t], unitNbrs,4)\n",
    "    if not (unbroken and noEnclave and abs(HDvPop[t] - aDP) < 0.05*aDP ):\n",
    "        print(\"ERROR for HD\",t,unbroken,noEnclave,HDvPop[t]/aDP,\"unbroken,noEnclave,HDvPop/aDP\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "id": "8fad08be-7da6-43c0-9223-26a53ac7c6a1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "save these unpatched results to temp file\n"
     ]
    }
   ],
   "source": [
    "print(\"save these unpatched results to temp file\")\n",
    "tList = [t for t in range(nHDs)]\n",
    "outDF = pd.DataFrame( {\"vtd\":tList,\"HDweight\":HDweight,\"HDvPop\":HDvPop,\"HDunitList\":HDunitList,\n",
    "                      \"splitUnitNo\":splitUnitNo,\"splitUnitFrac\":splitUnitFrac,\n",
    "                       \"centroid x\":HDCPx, \"centroid y\":HDCPy, \"homeU\":homeU, \"homeC\":homeC } )\n",
    "outname = STATE+str(int(nHDs))+\"_\"+str(nDistricts)+\"COI615goodPop.csv\" #\"contigUnpatchedB.csv\" unpatchedContigGoodPop.csv\n",
    "outpath = \"2024state_HD_output/\"+outname\n",
    "outDF.to_csv(outpath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "id": "9c2c48bf-55cc-4388-ae56-7c27108f5c18",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "optional restart.  Read in unpatched\n",
      "I read in a total of 8941 home district unit lists, of which 8934 are populated\n"
     ]
    }
   ],
   "source": [
    "############ OPTIONAL RESTART *******\n",
    "print(\"optional restart.  Read in unpatched\")\n",
    "inDF = pd.read_csv(\"./2024state_HD_output/OH8941_99COI615goodPop.csv\")\n",
    "HDweight, homeU, homeC = inDF[\"HDweight\"],inDF[\"homeU\"],inDF[\"homeC\"]\n",
    "splitUnitNo, splitUnitFrac = inDF[\"splitUnitNo\"],inDF[\"splitUnitFrac\"]\n",
    "nHDs = len(HDweight)\n",
    "popHDlist = list()\n",
    "for h in range(nHDs):\n",
    "    if HDweight[h] > 0:\n",
    "        popHDlist.append(h)\n",
    "unitString = inDF[\"HDunitList\"]\n",
    "HDunitList = [ast.literal_eval(unitString[h]) for h in range(nHDs)]\n",
    "print(\"I read in a total of\",nHDs,\"home district unit lists, of which\",len(popHDlist),\"are populated\")\n",
    "HDvPop = inDF[\"HDvPop\"].to_numpy()\n",
    "HDCPx, HDCPy = inDF[\"centroid x\"],inDF[\"centroid y\"]\n",
    "HDCP = [Point(HDCPx[h],HDCPy[h]) for h in range(nHDs)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "id": "9436e8b9-e204-41c0-96d3-b5eef5b118c3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "updating our unitUse\n",
      "unit use histogram\n"
     ]
    },
    {
     "data": {
      "image/png": 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Hw5o0aZI++uijNo/x+Xxyu92RzePxdHZMAABwmnNYlmV15sCf//zneumll/Taa69p8ODBHT7u+PHjGjlypGbNmqUHHnig1TWhUEihUCjydTAYlMfjUSAQkMvl6sy4QK8xtHiT6RF6hQOL80yPAJz2gsGg3G73SV+/bd0z8q358+dr48aN2r59u60QkaQzzjhD48aN0759+9pc43Q65XQ6OzMaAACIMbZ+TWNZlubPn69169bplVde0bBhw2w/YEtLi3bv3q20tDTbxwIAgPhj68pIYWGhysvLtWHDBiUlJcnv90uS3G63+vfvL0kqKChQenq6fD6fJOn+++/XxIkTNXz4cB05ckQPP/ywDh48qLlz53bxUwEAALHIVowsX75cknT11VdH7V+9erV++tOfSpLq6+vVp893F1y++OIL3XrrrfL7/RowYICysrK0Y8cOjRo16tQmBwAAcaHTN7D2pI7eAAOAG1h7CjewAifX0ddvPpsGAAAYRYwAAACjiBEAAGAUMQIAAIwiRgAAgFHECAAAMIoYAQAARhEjAADAKGIEAAAYRYwAAACjiBEAAGAUMQIAAIwiRgAAgFHECAAAMIoYAQAARhEjAADAKGIEAAAYRYwAAACjiBEAAGAUMQIAAIwiRgAAgFHECAAAMIoYAQAARhEjAADAKGIEAAAYRYwAAACjiBEAAGAUMQIAAIwiRgAAgFHECAAAMIoYAQAARhEjAADAKFsx4vP5dOWVVyopKUnJycnKz8/X3r17T3rc2rVrdemllyoxMVFjxozR5s2bOz0wAACIL7Zi5NVXX1VhYaHeeOMNVVZW6vjx47ruuuvU3Nzc5jE7duzQrFmzNGfOHNXW1io/P1/5+fnas2fPKQ8PAABin8OyLKuzB3/66adKTk7Wq6++qu9///utrpk5c6aam5u1cePGyL6JEycqMzNTK1as6NDjBINBud1uBQIBuVyuzo4L9ApDizeZHqFXOLA4z/QIwGmvo6/fp3TPSCAQkCQNHDiwzTXV1dXKycmJ2pebm6vq6uo2jwmFQgoGg1EbAACIT52OkXA4rIULF2ry5MkaPXp0m+v8fr9SUlKi9qWkpMjv97d5jM/nk9vtjmwej6ezYwIAgNNcp2OksLBQe/bsUUVFRVfOI0kqKSlRIBCIbIcOHeryxwAAAKeHhM4cNH/+fG3cuFHbt2/X4MGD212bmpqqxsbGqH2NjY1KTU1t8xin0ymn09mZ0QAAQIyxdWXEsizNnz9f69at0yuvvKJhw4ad9Biv16uqqqqofZWVlfJ6vfYmBQAAccnWlZHCwkKVl5drw4YNSkpKitz34Xa71b9/f0lSQUGB0tPT5fP5JEkLFixQdna2lixZory8PFVUVGjnzp1auXJlFz8VAAAQi2xdGVm+fLkCgYCuvvpqpaWlRbY1a9ZE1tTX16uhoSHy9aRJk1ReXq6VK1cqIyNDzz//vNavX9/uTa8AAKD3sHVlpCNvSbJt27YT9l1//fW6/vrr7TwUAADoJfhsGgAAYBQxAgAAjCJGAACAUcQIAAAwihgBAABGESMAAMAoYgQAABhFjAAAAKOIEQAAYBQxAgAAjCJGAACAUcQIAAAwihgBAABGESMAAMAoYgQAABhFjAAAAKOIEQAAYBQxAgAAjCJGAACAUcQIAAAwihgBAABGESMAAMAoYgQAABhFjAAAAKOIEQAAYBQxAgAAjCJGAACAUcQIAAAwKsH0AAAQi4YWbzI9gm0HFueZHgFoFVdGAACAUcQIAAAwynaMbN++XdOnT9egQYPkcDi0fv36dtdv27ZNDofjhM3v93d2ZgAAEEdsx0hzc7MyMjK0bNkyW8ft3btXDQ0NkS05OdnuQwMAgDhk+wbWadOmadq0abYfKDk5Weecc47t4wAAQHzrsXtGMjMzlZaWpqlTp+r1119vd20oFFIwGIzaAABAfOr2GElLS9OKFSv0wgsv6IUXXpDH49HVV1+tXbt2tXmMz+eT2+2ObB6Pp7vHBAAAhjgsy7I6fbDDoXXr1ik/P9/WcdnZ2RoyZIj+8pe/tPr9UCikUCgU+ToYDMrj8SgQCMjlcnV2XKBXiMX3v0DP4H1G0NOCwaDcbvdJX7+NvOnZ+PHj9dprr7X5fafTKafT2YMTAQAAU4y8z0hdXZ3S0tJMPDQAADjN2L4y0tTUpH379kW+/vDDD1VXV6eBAwdqyJAhKikp0ccff6ynn35akrR06VINGzZMl112mb766is99dRTeuWVV7R169auexYAACBm2Y6RnTt3asqUKZGvi4qKJEmzZ89WWVmZGhoaVF9fH/n+sWPH9Mtf/lIff/yxzjzzTI0dO1b/+Mc/on4GAADovU7pBtae0tEbYABwAyvaxg2s6Gkdff3ms2kAAIBRxAgAADCKGAEAAEYRIwAAwChiBAAAGEWMAAAAo4gRAABgFDECAACMIkYAAIBRxAgAADCKGAEAAEYRIwAAwChiBAAAGEWMAAAAo4gRAABgFDECAACMIkYAAIBRxAgAADCKGAEAAEYRIwAAwChiBAAAGEWMAAAAo4gRAABgFDECAACMIkYAAIBRxAgAADCKGAEAAEYRIwAAwChiBAAAGEWMAAAAo4gRAABgFDECAACMsh0j27dv1/Tp0zVo0CA5HA6tX7/+pMds27ZNl19+uZxOp4YPH66ysrJOjAoAAOKR7Rhpbm5WRkaGli1b1qH1H374ofLy8jRlyhTV1dVp4cKFmjt3rrZs2WJ7WAAAEH8S7B4wbdo0TZs2rcPrV6xYoWHDhmnJkiWSpJEjR+q1117T73//e+Xm5tp9eAAAEGdsx4hd1dXVysnJidqXm5urhQsXtnlMKBRSKBSKfB0MBrtrPKBdQ4s3mR4BAOJet9/A6vf7lZKSErUvJSVFwWBQX375ZavH+Hw+ud3uyObxeLp7TAAAYMhp+dc0JSUlCgQCke3QoUOmRwIAAN2k239Nk5qaqsbGxqh9jY2Ncrlc6t+/f6vHOJ1OOZ3O7h4NAACcBrr9yojX61VVVVXUvsrKSnm93u5+aAAAEANsx0hTU5Pq6upUV1cn6Zs/3a2rq1N9fb2kb37FUlBQEFk/b9487d+/X3fddZfee+89PfHEE3ruued0xx13dM0zAAAAMc12jOzcuVPjxo3TuHHjJElFRUUaN26c7rvvPklSQ0NDJEwkadiwYdq0aZMqKyuVkZGhJUuW6KmnnuLPegEAgCTJYVmWZXqIkwkGg3K73QoEAnK5XKbHQS/Cn/YinhxYnGd6BPQyHX39Pi3/mgYAAPQexAgAADCKGAEAAEYRIwAAwChiBAAAGEWMAAAAo4gRAABgFDECAACMIkYAAIBRxAgAADCKGAEAAEYRIwAAwChiBAAAGEWMAAAAo4gRAABgFDECAACMIkYAAIBRxAgAADCKGAEAAEYlmB4AANAzhhZvMj2CbQcW55keAT2AKyMAAMAoYgQAABhFjAAAAKOIEQAAYBQxAgAAjCJGAACAUcQIAAAwihgBAABGESMAAMAoYgQAABhFjAAAAKM6FSPLli3T0KFDlZiYqAkTJujNN99sc21ZWZkcDkfUlpiY2OmBAQBAfLEdI2vWrFFRUZFKS0u1a9cuZWRkKDc3V4cPH27zGJfLpYaGhsh28ODBUxoaAADED9sx8uijj+rWW2/VLbfcolGjRmnFihU688wztWrVqjaPcTgcSk1NjWwpKSmnNDQAAIgftmLk2LFjqqmpUU5Oznc/oE8f5eTkqLq6us3jmpqadMEFF8jj8WjGjBl6++23232cUCikYDAYtQEAgPhkK0Y+++wztbS0nHBlIyUlRX6/v9VjRowYoVWrVmnDhg165plnFA6HNWnSJH300UdtPo7P55Pb7Y5sHo/HzpgAACCGdPtf03i9XhUUFCgzM1PZ2dl68cUXdf755+vJJ59s85iSkhIFAoHIdujQoe4eEwAAGJJgZ/F5552nvn37qrGxMWp/Y2OjUlNTO/QzzjjjDI0bN0779u1rc43T6ZTT6bQzGgAAiFG2roz069dPWVlZqqqqiuwLh8OqqqqS1+vt0M9oaWnR7t27lZaWZm9SAAAQl2xdGZGkoqIizZ49W1dccYXGjx+vpUuXqrm5WbfccoskqaCgQOnp6fL5fJKk+++/XxMnTtTw4cN15MgRPfzwwzp48KDmzp3btc8EAADEJNsxMnPmTH366ae677775Pf7lZmZqZdffjlyU2t9fb369PnugssXX3yhW2+9VX6/XwMGDFBWVpZ27NihUaNGdd2zAAAAMcthWZZleoiTCQaDcrvdCgQCcrlcpsdBLzK0eJPpEYBe7cDiPNMj4BR09PWbz6YBAABGESMAAMAoYgQAABhFjAAAAKOIEQAAYBQxAgAAjCJGAACAUcQIAAAwihgBAABGESMAAMAoYgQAABhFjAAAAKOIEQAAYFSC6QEAAGhLLH5yNp80bB9XRgAAgFHECAAAMIoYAQAARhEjAADAKGIEAAAYRYwAAACj+NNe9IhY/PM8AEDP4MoIAAAwihgBAABGESMAAMAoYgQAABhFjAAAAKOIEQAAYBQxAgAAjCJGAACAUcQIAAAwindgBQCgC8XiO04fWJxn9PE7dWVk2bJlGjp0qBITEzVhwgS9+eab7a5fu3atLr30UiUmJmrMmDHavHlzp4YFAADxx3aMrFmzRkVFRSotLdWuXbuUkZGh3NxcHT58uNX1O3bs0KxZszRnzhzV1tYqPz9f+fn52rNnzykPDwAAYp/DsizLzgETJkzQlVdeqccff1ySFA6H5fF4dPvtt6u4uPiE9TNnzlRzc7M2btwY2Tdx4kRlZmZqxYoVHXrMYDAot9utQCAgl8tlZ1ycJmLxsiUA9Bbd9Wuajr5+27pn5NixY6qpqVFJSUlkX58+fZSTk6Pq6upWj6murlZRUVHUvtzcXK1fv77NxwmFQgqFQpGvA4GApG+eFKTRpVtMjwAAiCPd9fr67c892XUPWzHy2WefqaWlRSkpKVH7U1JS9N5777V6jN/vb3W93+9v83F8Pp8WLVp0wn6Px2NnXAAA0AHupd37848ePSq3293m90/Lv6YpKSmJupoSDof1+eef69xzz5XD4TA42ekpGAzK4/Ho0KFD/Bqrh3HuzeHcm8X5NyeWzr1lWTp69KgGDRrU7jpbMXLeeeepb9++amxsjNrf2Nio1NTUVo9JTU21tV6SnE6nnE5n1L5zzjnHzqi9ksvlOu3/w4xXnHtzOPdmcf7NiZVz394VkW/Z+muafv36KSsrS1VVVZF94XBYVVVV8nq9rR7j9Xqj1ktSZWVlm+sBAEDvYvvXNEVFRZo9e7auuOIKjR8/XkuXLlVzc7NuueUWSVJBQYHS09Pl8/kkSQsWLFB2draWLFmivLw8VVRUaOfOnVq5cmXXPhMAABCTbMfIzJkz9emnn+q+++6T3+9XZmamXn755chNqvX19erT57sLLpMmTVJ5ebnuvfde3X333br44ou1fv16jR49uuueRS/ndDpVWlp6wq+20P049+Zw7s3i/JsTj+fe9vuMAAAAdCU+KA8AABhFjAAAAKOIEQAAYBQxAgAAjCJGYsSyZcs0dOhQJSYmasKECXrzzTfbXX/kyBEVFhYqLS1NTqdTl1xyiTZv3txD08YXu+d+6dKlGjFihPr37y+Px6M77rhDX331VQ9NGz+2b9+u6dOna9CgQXI4HO1+ntW3tm3bpssvv1xOp1PDhw9XWVlZt88Zj+ye+xdffFFTp07V+eefL5fLJa/Xqy1b+AytzujMf/ffev3115WQkKDMzMxum6+7ECMxYM2aNSoqKlJpaal27dqljIwM5ebm6vDhw62uP3bsmKZOnaoDBw7o+eef1969e/XHP/5R6enpPTx57LN77svLy1VcXKzS0lK9++67+tOf/qQ1a9bo7rvv7uHJY19zc7MyMjK0bNmyDq3/8MMPlZeXpylTpqiurk4LFy7U3LlzeVHsBLvnfvv27Zo6dao2b96smpoaTZkyRdOnT1dtbW03Txp/7J77bx05ckQFBQW69tpru2mybmbhtDd+/HirsLAw8nVLS4s1aNAgy+fztbp++fLl1oUXXmgdO3asp0aMW3bPfWFhoXXNNddE7SsqKrImT57crXPGO0nWunXr2l1z1113WZdddlnUvpkzZ1q5ubndOFn868i5b82oUaOsRYsWdf1AvYidcz9z5kzr3nvvtUpLS62MjIxunas7cGXkNHfs2DHV1NQoJycnsq9Pnz7KyclRdXV1q8f87W9/k9frVWFhoVJSUjR69Gj99re/VUtLS0+NHRc6c+4nTZqkmpqayK9y9u/fr82bN+uHP/xhj8zcm1VXV0f9W0lSbm5um/9W6D7hcFhHjx7VwIEDTY/SK6xevVr79+9XaWmp6VE67bT81F5857PPPlNLS0vkHW6/lZKSovfee6/VY/bv369XXnlFN910kzZv3qx9+/bpF7/4hY4fPx7T/7H2tM6c+xtvvFGfffaZrrrqKlmWpa+//lrz5s3j1zQ9wO/3t/pvFQwG9eWXX6p///6GJut9HnnkETU1NemGG24wPUrc++CDD1RcXKx//etfSkiI3Zd0rozEoXA4rOTkZK1cuVJZWVmaOXOm7rnnHq1YscL0aHFv27Zt+u1vf6snnnhCu3bt0osvvqhNmzbpgQceMD0a0CPKy8u1aNEiPffcc0pOTjY9TlxraWnRjTfeqEWLFumSSy4xPc4pid2M6iXOO+889e3bV42NjVH7GxsblZqa2uoxaWlpOuOMM9S3b9/IvpEjR8rv9+vYsWPq169ft84cLzpz7n/961/r5ptv1ty5cyVJY8aMUXNzs2677Tbdc889UZ/bhK6Vmpra6r+Vy+XiqkgPqaio0Ny5c7V27doTfmWGrnf06FHt3LlTtbW1mj9/vqRv/s+oZVlKSEjQ1q1bdc011xiesmP4X8bTXL9+/ZSVlaWqqqrIvnA4rKqqKnm93laPmTx5svbt26dwOBzZ9/777ystLY0QsaEz5/5///vfCcHxbRRafAxUt/J6vVH/VpJUWVnZ5r8Vutazzz6rW265Rc8++6zy8vJMj9MruFwu7d69W3V1dZFt3rx5GjFihOrq6jRhwgTTI3ac4Rto0QEVFRWW0+m0ysrKrHfeece67bbbrHPOOcfy+/2WZVnWzTffbBUXF0fW19fXW0lJSdb8+fOtvXv3Whs3brSSk5OtBx980NRTiFl2z31paamVlJRkPfvss9b+/futrVu3WhdddJF1ww03mHoKMevo0aNWbW2tVVtba0myHn30Uau2ttY6ePCgZVmWVVxcbN18882R9fv377fOPPNM684777Teffdda9myZVbfvn2tl19+2dRTiFl2z/1f//pXKyEhwVq2bJnV0NAQ2Y4cOWLqKcQsu+f+/xerf01DjMSIP/zhD9aQIUOsfv36WePHj7feeOONyPeys7Ot2bNnR63fsWOHNWHCBMvpdFoXXnih9dBDD1lff/11D08dH+yc++PHj1u/+c1vrIsuushKTEy0PB6P9Ytf/ML64osven7wGPfPf/7TknTC9u35nj17tpWdnX3CMZmZmVa/fv2sCy+80Fq9enWPzx0P7J777Ozsdtej4zrz3/3/Fasx4rAsrh0DAABzuGcEAAAYRYwAAACjiBEAAGAUMQIAAIwiRgAAgFHECAAAMIoYAQAARhEjAADAKGIEAAAYRYwAAACjiBEAAGAUMQIAAIz6f9iQPV39p01NAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "current avg use and its sd are 1.00017 0.11109\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"updating our unitUse\")\n",
    "unitUse = [0.]*nUnits\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += nDistricts * HDweight[t]\n",
    "    if splitUnitNo[t] >= 0 :\n",
    "        unitUse[splitUnitNo[t]] -= (1. - splitUnitFrac[t]) * nDistricts * HDweight[t]\n",
    "print(\"unit use histogram\")\n",
    "plt.hist(unitUse, weights = unitPop)\n",
    "plt.show()\n",
    "\n",
    "activeUnitDistro, activeUnitWeights = list(), list()\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] > 0.1:\n",
    "        activeUnitDistro.append(unitUse[u])\n",
    "        activeUnitWeights.append(unitPop[u]/statePop)\n",
    "plt.hist(activeUnitDistro, weights=activeUnitWeights, bins = 20, histtype = \"step\")\n",
    "#plt.show()\n",
    "currAvg, currSD = getWeightedAvgAndSD(activeUnitDistro, activeUnitWeights)\n",
    "print(\"current avg use and its sd are\",r5(currAvg),r5(currSD) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "id": "78d8647b-5421-4a27-889f-27315e9e7695",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "... and our usage vs. pop\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"... and our usage vs. pop\")\n",
    "plt.scatter(unitPop,unitUse)\n",
    "plt.show()\n",
    "prepatchedUnitUse = unitUse.copy() #safekeeping"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "id": "0dd75303-2a1a-4d1d-a9ad-6962da74e2cd",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "we will freeze (avoid patching) 0 HDs with a split unit\n"
     ]
    }
   ],
   "source": [
    "hasSplitUnit = list()\n",
    "for h in range(nHDs):\n",
    "    if splitUnitNo[h] >= 0 :\n",
    "        hasSplitUnit.append(h)\n",
    "print(\"we will freeze (avoid patching)\",len(hasSplitUnit),\"HDs with a split unit\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "id": "49a4f6d9-845b-4bcb-a4d3-433fe780ee99",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "working on avg unit-to-HDcp dist for HD 0\n",
      "working on avg unit-to-HDcp dist for HD 1502\n",
      "working on avg unit-to-HDcp dist for HD 3003\n",
      "working on avg unit-to-HDcp dist for HD 4505\n",
      "working on avg unit-to-HDcp dist for HD 6006\n",
      "working on avg unit-to-HDcp dist for HD 7506\n",
      "all unit-toHDcp distances computed\n"
     ]
    }
   ],
   "source": [
    "barredJettisonSet = set([]) #for basic muni snap, there are no special corner units to freeze\n",
    "avgDist = [0. for t in range(nHDs)]  #about 6sec per 1000 HDs\n",
    "for i,t in enumerate(popHDlist):\n",
    "    if i%1500 == 0:\n",
    "        print(\"working on avg unit-to-HDcp dist for HD\",t)\n",
    "    avgDist[t] =  np.sum([unitPop[u]*unitCP[u].distance(HDCP[t]) for u in HDunitList[t] ]) / HDvPop[t]\n",
    "print(\"all unit-toHDcp distances computed\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "id": "820f5f1e-f449-4cfb-94fc-96d1aab07674",
   "metadata": {},
   "outputs": [],
   "source": [
    "hdCP = HDCP.copy() #nomenclature"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 135,
   "id": "e5bba0ce-dc4a-494e-86b3-0fbefed0e032",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "For now, we will disallow (freeze) HDs from patching.\n",
      "Start with underpatching. This algorithm simplified vs. vanillaHD to manage blockiness.\n",
      "Currently, we will stop patching when the overall sd of usage is less than 0.07\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter updated maxSD value 0.07\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "this would currently cover a total of 1142 units\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter updated number of units to try boosting usage 300\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "there are currently 1998 units out of 3099 with usage below 0.98\n",
      "maxExchangePop is currently 0.15 fraction of avgDistrictPop\n",
      "Let's further tighten the distro with exchanges up to 117994 = aDP* 0.15\n",
      "current avg and SD of unit usage are 1.00018 0.10929 . Now trying to increase up to 300 units' underusage\n",
      "try to add unit 2360 from 0 th HD.  Usage up to 0.5564446743608702\n",
      "try to add unit 2360 from 100 th HD.  Usage up to 0.5646569229338518\n",
      "try to add unit 2360 from 200 th HD.  Usage up to 0.6068381334447005\n",
      "try to add unit 2360 from 300 th HD.  Usage up to 0.6271335743839669\n",
      "try to add unit 2360 from 400 th HD.  Usage up to 0.6497503103533032\n",
      "try to add unit 2360 from 500 th HD.  Usage up to 0.6662116736306322\n",
      "try to add unit 2360 from 600 th HD.  Usage up to 0.6813471274247385\n",
      "try to add unit 2360 from 700 th HD.  Usage up to 0.6950193771774362\n",
      "try to add unit 2360 from 800 th HD.  Usage up to 0.7130634416116307\n",
      "try to add unit 2360 from 900 th HD.  Usage up to 0.7245364359415329\n",
      "try to add unit 2360 from 1000 th HD.  Usage up to 0.7333919349445366\n",
      "try to add unit 2360 from 1100 th HD.  Usage up to 0.7457662426240091\n",
      "try to add unit 2360 from 1200 th HD.  Usage up to 0.7672350435374036\n",
      "try to add unit 2360 from 1300 th HD.  Usage up to 0.7743934292517167\n",
      "try to add unit 2360 from 1400 th HD.  Usage up to 0.7883555230716933\n",
      "try to add unit 2360 from 1500 th HD.  Usage up to 0.7932218524118447\n",
      "try to add unit 2360 from 1600 th HD.  Usage up to 0.8020900638739368\n",
      "try to add unit 2360 from 1700 th HD.  Usage up to 0.8073326820031893\n",
      "try to add unit 2360 from 1800 th HD.  Usage up to 0.8146398034888712\n",
      "try to add unit 2360 from 1900 th HD.  Usage up to 0.8225329693386603\n",
      "all done trying2increase usage of unit 2360 final usage = 0.82519 6384 sec elapsed 160 566 complete, failed patches, unstarted= 1198\n",
      "current avg and SD of usage are 1.00019 0.10432\n",
      "try to add unit 88 from 0 th HD.  Usage up to 0.5704245656236253\n",
      "try to add unit 88 from 100 th HD.  Usage up to 0.5801267144021063\n",
      "try to add unit 88 from 200 th HD.  Usage up to 0.5936273459570719\n",
      "try to add unit 88 from 300 th HD.  Usage up to 0.6012764325923073\n",
      "try to add unit 88 from 400 th HD.  Usage up to 0.6054257792397088\n",
      "try to add unit 88 from 500 th HD.  Usage up to 0.6194501641092336\n",
      "all done trying2increase usage of unit 88 final usage = 0.65374 12541 sec elapsed 48 527 complete, failed patches, unstarted= 11\n",
      "current avg and SD of usage are 1.0002 0.10259\n",
      "try to add unit 743 from 0 th HD.  Usage up to 0.5962575537430683\n",
      "try to add unit 743 from 100 th HD.  Usage up to 0.6056012111751775\n",
      "try to add unit 743 from 200 th HD.  Usage up to 0.6344966306897128\n",
      "try to add unit 743 from 300 th HD.  Usage up to 0.6682494808230333\n",
      "try to add unit 743 from 400 th HD.  Usage up to 0.6915755720096661\n",
      "try to add unit 743 from 500 th HD.  Usage up to 0.7390311817975056\n",
      "all done trying2increase usage of unit 743 final usage = 0.77352 20136 sec elapsed 107 469 complete, failed patches, unstarted= 18\n",
      "current avg and SD of usage are 1.00024 0.10067\n",
      "try to add unit 350 from 0 th HD.  Usage up to 0.6431309329045057\n",
      "try to add unit 350 from 100 th HD.  Usage up to 0.6431309329045057\n",
      "try to add unit 350 from 200 th HD.  Usage up to 0.6558332220285376\n",
      "try to add unit 350 from 300 th HD.  Usage up to 0.6898937136718626\n",
      "try to add unit 350 from 400 th HD.  Usage up to 0.7118010944239042\n",
      "try to add unit 350 from 500 th HD.  Usage up to 0.7439763283839915\n",
      "try to add unit 350 from 600 th HD.  Usage up to 0.7652163050337392\n",
      "try to add unit 350 from 700 th HD.  Usage up to 0.8165148912048689\n",
      "try to add unit 350 from 800 th HD.  Usage up to 0.84303308086933\n",
      "try to add unit 350 from 900 th HD.  Usage up to 0.8891831211084902\n",
      "try to add unit 350 from 1000 th HD.  Usage up to 0.9116078989455465\n",
      "try to add unit 350 from 1100 th HD.  Usage up to 0.944960306617489\n",
      "try to add unit 350 from 1200 th HD.  Usage up to 0.9481346076525865\n",
      "try to add unit 350 from 1300 th HD.  Usage up to 0.9562108329132909\n",
      "try to add unit 350 from 1400 th HD.  Usage up to 0.9611394533029903\n",
      "all done trying2increase usage of unit 350 final usage = 0.96114 22450 sec elapsed 162 177 complete, failed patches, unstarted= 1115\n",
      "current avg and SD of usage are 1.00025 0.09536\n",
      "try to add unit 2816 from 0 th HD.  Usage up to 0.6998577391076028\n",
      "try to add unit 2816 from 100 th HD.  Usage up to 0.7054817310095955\n",
      "try to add unit 2816 from 200 th HD.  Usage up to 0.7191082159095614\n",
      "try to add unit 2816 from 300 th HD.  Usage up to 0.7671447850778639\n",
      "try to add unit 2816 from 400 th HD.  Usage up to 0.7845443278361299\n",
      "try to add unit 2816 from 500 th HD.  Usage up to 0.7904530788217671\n",
      "try to add unit 2816 from 600 th HD.  Usage up to 0.7975529872242586\n",
      "try to add unit 2816 from 700 th HD.  Usage up to 0.8007171182920835\n",
      "try to add unit 2816 from 800 th HD.  Usage up to 0.8007171182920835\n",
      "try to add unit 2816 from 900 th HD.  Usage up to 0.8101802728396503\n",
      "try to add unit 2816 from 1000 th HD.  Usage up to 0.823871591280984\n",
      "try to add unit 2816 from 1100 th HD.  Usage up to 0.8426580633261123\n",
      "try to add unit 2816 from 1200 th HD.  Usage up to 0.8497643279581527\n",
      "try to add unit 2816 from 1300 th HD.  Usage up to 0.8577808046611279\n",
      "try to add unit 2816 from 1400 th HD.  Usage up to 0.8638408339099534\n",
      "try to add unit 2816 from 1500 th HD.  Usage up to 0.8738913040675375\n",
      "try to add unit 2816 from 1600 th HD.  Usage up to 0.879497498526802\n",
      "try to add unit 2816 from 1700 th HD.  Usage up to 0.8830493595969131\n",
      "try to add unit 2816 from 1800 th HD.  Usage up to 0.8889174307134596\n",
      "all done trying2increase usage of unit 2816 final usage = 0.89051 30094 sec elapsed 111 446 complete, failed patches, unstarted= 1303\n",
      "current avg and SD of usage are 1.00025 0.09396\n",
      "try to add unit 1136 from 0 th HD.  Usage up to 0.7037172416877759\n",
      "try to add unit 1136 from 100 th HD.  Usage up to 0.7037172416877759\n",
      "try to add unit 1136 from 200 th HD.  Usage up to 0.718215801281409\n",
      "try to add unit 1136 from 300 th HD.  Usage up to 0.727789554223071\n",
      "try to add unit 1136 from 400 th HD.  Usage up to 0.7403672612480057\n",
      "all done trying2increase usage of unit 1136 final usage = 0.77913 35097 sec elapsed 39 437 complete, failed patches, unstarted= 18\n",
      "current avg and SD of usage are 1.00026 0.0935\n",
      "try to add unit 876 from 0 th HD.  Usage up to 0.7134854952535427\n",
      "try to add unit 876 from 100 th HD.  Usage up to 0.7337707662255367\n",
      "try to add unit 876 from 200 th HD.  Usage up to 0.7619987816377796\n",
      "all done trying2increase usage of unit 876 final usage = 0.77847 36204 sec elapsed 40 13 complete, failed patches, unstarted= 200\n",
      "current avg and SD of usage are 1.00027 0.09304\n",
      "try to add unit 1135 from 0 th HD.  Usage up to 0.7231901865238287\n"
     ]
    },
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "Cell \u001b[1;32mIn[135], line 98\u001b[0m\n\u001b[0;32m     96\u001b[0m listNo \u001b[38;5;241m=\u001b[39m idx[ij]   \u001b[38;5;66;03m#work from low to high score\u001b[39;00m\n\u001b[0;32m     97\u001b[0m addU \u001b[38;5;241m=\u001b[39m addCandidates[listNo]\n\u001b[1;32m---> 98\u001b[0m cContig \u001b[38;5;241m=\u001b[39m \u001b[43mwontEnclave\u001b[49m\u001b[43m(\u001b[49m\u001b[43maddU\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mlist\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mtrySet\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43munitNbrs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mborderUnits\u001b[49m\u001b[43m)\u001b[49m  \u001b[38;5;66;03m#4/20/24 sub this in as faster? vs below line\u001b[39;00m\n\u001b[0;32m     99\u001b[0m \u001b[38;5;66;03m#contig,cContig, __, ___ = enclaveCheck(list(trySet.union({addU}) ), unitNbrs)  #4/20/24 this is unnec slow\u001b[39;00m\n\u001b[0;32m    100\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m cContig: \u001b[38;5;66;03m#contig and cContig:\u001b[39;00m\n",
      "Cell \u001b[1;32mIn[1], line 205\u001b[0m, in \u001b[0;36mwontEnclave\u001b[1;34m(proposedU, dList, NBRLIST, mapBDRYLIST)\u001b[0m\n\u001b[0;32m    203\u001b[0m                 adjSet \u001b[38;5;241m=\u001b[39m adjSet\u001b[38;5;241m.\u001b[39munion( \u001b[38;5;28mset\u001b[39m(NBRLIST[UU])\u001b[38;5;241m.\u001b[39mdifference(\u001b[38;5;28mset\u001b[39m(newList)) )\n\u001b[0;32m    204\u001b[0m             ADJLIST \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mlist\u001b[39m(adjSet)\n\u001b[1;32m--> 205\u001b[0m             wontEnclave, __ \u001b[38;5;241m=\u001b[39m   \u001b[43misContiguous\u001b[49m\u001b[43m(\u001b[49m\u001b[43mADJLIST\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mNBRLIST\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    207\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m wontEnclave\n",
      "Cell \u001b[1;32mIn[1], line -1\u001b[0m, in \u001b[0;36misContiguous\u001b[1;34m(VLIST, NEIGHBORLIST, returnBiggestPiece)\u001b[0m\n\u001b[0;32m      0\u001b[0m <Error retrieving source code with stack_data see ipython/ipython#13598>\n",
      "\u001b[1;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],
   "source": [
    "print(\"For now, we will disallow (freeze) HDs from patching.\")\n",
    "print(\"Start with underpatching. This algorithm simplified vs. vanillaHD to manage blockiness.\")\n",
    "\n",
    "maxSD = 0.07  #0.055   #adjust down if distro already tight\n",
    "print(\"Currently, we will stop patching when the overall sd of usage is less than\",maxSD)\n",
    "maxSD = float(input(\"enter updated maxSD value\"))\n",
    "stopMinUse = 1. - maxSD\n",
    "#print(\"we will stop patching on individual underused units when their usage exceeds\",r5(stopMinUse))\n",
    "maxNtries = 0\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] < stopMinUse:\n",
    "        maxNtries +=1\n",
    "print(\"this would currently cover a total of\",maxNtries,\"units\")\n",
    "maxNtries = int(input(\"enter updated number of units to try boosting usage\"))\n",
    "stopMinUse = 0.98 #float(input(\"enter updated stopMinUse value for ending usage boost on a unit; I reco 0.98\"))\n",
    "nInPlay = 0\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] < stopMinUse:\n",
    "        nInPlay +=1\n",
    "print(\"there are currently\",nInPlay,\"units out of\",nUnits,\"with usage below\",stopMinUse)\n",
    "maxExchangePop = 0.15*aDP #this is widened vs. vanillaHD to overcome blockiness\n",
    "print(\"maxExchangePop is currently\",r5(maxExchangePop/aDP),\"fraction of avgDistrictPop\")\n",
    "debug1 = 10 #int(input(\"enter 1 to print out stats for every patched HD, otherwise enter reporting frequency\"))\n",
    "print(\"Let's further tighten the distro with exchanges up to\",int(maxExchangePop),\"= aDP*\",r3(maxExchangePop/aDP) ) \n",
    "maxGap = aDP - minDistrictPop  #0.9 * np.median(unitPop)   #aDP - minDistrictPop  \n",
    "currAvg, currSD = getWeightedAvgAndSD(unitUse,unitPop)\n",
    "nonfrozenList = list(  set(popHDlist).difference( set(hasSplitUnit) )  )\n",
    "\n",
    "attemptedSmallUs, startTime = list(), time.time()\n",
    "print(\"current avg and SD of unit usage are\",r5(currAvg), r5(currSD),\". Now trying to increase up to\",maxNtries,\"units' underusage\" )\n",
    "startTime = time.time()\n",
    "while currSD > maxSD and len(attemptedSmallUs) < maxNtries:\n",
    "    #simplified vs. vanillaHD - always work on the lowest-used unit.\n",
    "    eligUnitUse = unitUse.copy()\n",
    "    for u in range(nUnits):\n",
    "        if u in attemptedSmallUs: #we already tried this one, so lock it out\n",
    "            eligUnitUse[u] = 999.  #preventing re-selection\n",
    "    UUU = eligUnitUse.index(np.min(eligUnitUse))\n",
    "    attemptedSmallUs.append(UUU)\n",
    "    UUUc = [UUU] + unitNbrs[UUU]\n",
    "    if len(attemptedSmallUs) % debug1 == 0:\n",
    "        print(\"begin usage increase for unit\",UUU,\"with usage\",r5(unitUse[UUU]),\". Sec, total UU units tried =\",\n",
    "              int(time.time()-startTime),len(attemptedSmallUs) )\n",
    "    for u in UUUc.copy():\n",
    "        if unitUse[u] > 1.:\n",
    "            UUUc.remove(u)  #...drop any overused neighbors of the primary UUU from the target sheddable cluster\n",
    "    uuuHDs, uuuDists, UUUcSet = list(), list(), set(UUUc)\n",
    "    for t in nonfrozenList: #popHDlist:  #finding all HDs with at least one cluster member on the boundary\n",
    "        if UUU not in HDunitList[t]:\n",
    "            HDadjoinSet = set( getAdjoiners(HDunitList[t],unitNbrs) )\n",
    "            if len(HDadjoinSet.intersection(UUUcSet) ) > 0: #the UUU or one of its underused 1-neighbors adjoins this HD\n",
    "                uuuHDs.append(t)  #Note: we'll check later if we can contiguously pick up the UUU's cluster\n",
    "                uuuDists.append( unitCP[UUU].distance(hdCP[t]) / avgDist[t] )\n",
    "        idx0 = np.argsort(uuuDists)\n",
    "    hasCandidates = True\n",
    "    if len(uuuDists) == 0:  #this underused unit is buried inside others; skip it\n",
    "        hasCandidates = False\n",
    "        print(\"   Couldn't find any HDs adjacent to underused unit\",UUU)\n",
    "    nPatchSuccess, nPatchFail, nCouldntStart, idxNo = 0,0,0,-1\n",
    "    while unitUse[UUU] < stopMinUse and idxNo < 0.8*len(uuuHDs) and hasCandidates: #arbitrarily only examine 80% closest of HDs\n",
    "        excess, giveUpOnShedding = 99*aDP, True  #default = failed swap\n",
    "        idxNo += 1\n",
    "        if idxNo % 100 == 0 : #and debug1 == 1:\n",
    "            print(\"try to add unit\",UUU,\"from\",abs(idxNo),\"th HD.  Usage up to\",unitUse[UUU] )\n",
    "        t = uuuHDs[idx0[idxNo]]\n",
    "        trySet = set(HDunitList[t]).union(UUUcSet)\n",
    "        tryPop = np.sum([unitPop[u] for u in trySet])\n",
    "        contig,complementContig, __, ___ = enclaveCheck(list(trySet), unitNbrs)\n",
    "        loopUUUc = UUUc.copy()  #default; we will add whole cluster\n",
    "        if not (contig and complementContig and tryPop < aDP + maxExchangePop): \n",
    "            #we can't add whole cluster; neighbors may be enclavy or too much pop.   Try just adding the UUU\n",
    "            trySet = set(HDunitList[t]).union({UUU})\n",
    "            contig,complementContig, __, ___ = enclaveCheck(list(trySet), unitNbrs)\n",
    "            loopUUUc = [UUU]\n",
    "        if contig and complementContig:  #we can at least add the cluster, let's go for more\n",
    "            HDuuuSet = set(loopUUUc).difference(set(HDunitList[t]))  #the subset of the UUU cluster that adjoins (NOT in) this HD\n",
    "            HDuuuCpop = np.sum([unitPop[u] for u in HDuuuSet])\n",
    "            giveUpOnAdding = False            \n",
    "            addCandidates, addUseDists = list(), list()\n",
    "            uuCandidates = getAdjoiners(trySet, unitNbrs)  #any adjoiner can be picked up, even if far from UUUc\n",
    "            for u in uuCandidates:\n",
    "                if HDuuuCpop + unitPop[u] <= maxExchangePop:\n",
    "                    addCandidates.append(u)  #Below's relative scoring of use and distance is a bit arbitrary\n",
    "                    addUseDists.append((unitUse[uu]-1.) + 0.1*unitCP[uu].distance(hdCP[t]) / avgDist[t])  #bias toward close, underused\n",
    "            if len(addCandidates) == 0:\n",
    "                giveUpOnAdding = True\n",
    "            while HDuuuCpop < maxExchangePop and not giveUpOnAdding:\n",
    "                addNneighbors = [len( set(unitNbrs[addC]).intersection(trySet) ) for addC in addCandidates ]\n",
    "                addScores = addUseDists.copy()\n",
    "                for jjj, u in enumerate(addCandidates):\n",
    "                    if addNneighbors[jjj] == 1:\n",
    "                        addScores[jjj] += 0.4321    #discourage growing fingers\n",
    "                #print(\"HDuuuCpop is now\",HDuuuCpop)\n",
    "                idx, ij, notYetPicked = np.argsort(addScores), 0, True\n",
    "                while ij < 0.5*len(addScores) and notYetPicked:\n",
    "                    listNo = idx[ij]   #work from low to high score\n",
    "                    addU = addCandidates[listNo]\n",
    "                    cContig = wontEnclave(addU, list(trySet), unitNbrs, borderUnits)  #4/20/24 sub this in as faster? vs below line\n",
    "                    #contig,cContig, __, ___ = enclaveCheck(list(trySet.union({addU}) ), unitNbrs)  #4/20/24 this is unnec slow\n",
    "                    if cContig: #contig and cContig:\n",
    "                        notYetPicked = False\n",
    "                        HDuuuCpop += unitPop[addU]\n",
    "                        HDuuuSet.add(addU)\n",
    "                        trySet.add(addU)\n",
    "                        del addUseDists[addCandidates.index(addU)]\n",
    "                        del addCandidates[addCandidates.index(addU)]                        \n",
    "                        for uu in list(set(unitNbrs[addU]).difference(trySet) ): \n",
    "                            if uu not in addCandidates and unitPop[uu] + HDuuuCpop < maxExchangePop and unitUse[uu] < 1.01:\n",
    "                                addCandidates.append(uu)\n",
    "                                addUseDists.append( (unitUse[uu]-1.) + 0.1*unitCP[uu].distance(hdCP[t]) / avgDist[t] )\n",
    "                    else:\n",
    "                        ij +=1\n",
    "                if notYetPicked:\n",
    "                    giveUpOnAdding = True  #all candidates would create a discontig, so can't shed any more units\n",
    "            addSet = HDuuuSet.copy()  #we're done building the list of underused units to add to this HD\n",
    "            trySet = set(HDunitList[t]).union(addSet) \n",
    "            excess = np.sum([unitPop[u] for u in trySet]) - aDP\n",
    "            shedCandidates, shedScores, giveUpOnShedding = list(), list(), False\n",
    "            bdryCandidates = getBdryNonEdgers(trySet, unitNbrs)  #new - any boundary unit can be shed, even if far from OUUc\n",
    "            for u in bdryCandidates:\n",
    "                if unitPop[u] <= excess + maxGap and u != homeU[t]:\n",
    "                    shedCandidates.append(u)\n",
    "                    shedScores.append((unitUse[u] - 1.) * unitCP[u].distance(hdCP[t])/avgDist[t])  #bias toward OVERUSED, far\n",
    "            if len(shedCandidates) == 0:\n",
    "                giveUpOnShedding = True\n",
    "            shedSet = set()\n",
    "            while excess > maxGap and not giveUpOnShedding:\n",
    "                #print(\"excess pop is now\",excess,\"for HD\",t)\n",
    "                idx, ij, notYetPicked = np.argsort(shedScores), 0, True\n",
    "                while ij < len(shedScores) and notYetPicked:\n",
    "                    listNo = idx[-1-ij]   #work from high to low score\n",
    "                    shedU = shedCandidates[listNo]\n",
    "                    if shedScores[listNo] <= 0:  #we're delving into the underused; stop adding to shed list\n",
    "                        break\n",
    "                    if excess - unitPop[shedU] >= -1*maxGap:\n",
    "                        contig,cContig, __, ___ = enclaveCheck(list(trySet.difference({shedU}) ), unitNbrs)\n",
    "                        if contig and cContig:\n",
    "                            notYetPicked = False\n",
    "                            excess -= unitPop[shedU]\n",
    "                            trySet.remove(shedU)\n",
    "                            shedSet.add(shedU)\n",
    "                            del shedScores[shedCandidates.index(shedU)]\n",
    "                            del shedCandidates[shedCandidates.index(shedU)]\n",
    "                            newSheddables = set(unitNbrs[shedU]).intersection(trySet)\n",
    "                            for u in newSheddables:\n",
    "                                if excess - unitPop[u] >= -1*maxGap and u not in shedCandidates + [homeU[t]]:\n",
    "                                    shedCandidates.append(u)  #we'll check enclavity if ever picked\n",
    "                                    shedScores.append((unitUse[u] - 1.) * unitCP[u].distance(hdCP[t])/avgDist[t])\n",
    "                            for kkk, u in enumerate(shedCandidates): #checking if this shed eliminates high-pop future sheds ...\n",
    "                                if excess - unitPop[u] < -1*maxGap:\n",
    "                                    del shedScores[kkk]\n",
    "                                    del shedCandidates[kkk]\n",
    "                    ij +=1\n",
    "                if notYetPicked:\n",
    "                    giveUpOnShedding = True  #all shedcandidates would create a discontig, so can't shed enough units to square pop\n",
    "            legitSwap = False\n",
    "            currPop = np.sum([ unitPop[u] for u in trySet] )\n",
    "            if abs(currPop - aDP) <= maxGap: \n",
    "                contig,cContig, __, ___ = enclaveCheck(list(trySet), unitNbrs) \n",
    "                if contig and cContig:\n",
    "                    legitSwap = True\n",
    "            if legitSwap:\n",
    "                for u in shedSet:\n",
    "                    unitUse[u] -= HDweight[t] * nDistricts\n",
    "                for u in addSet:\n",
    "                    unitUse[u] += HDweight[t] * nDistricts\n",
    "                HDunitList[t] = list(trySet)\n",
    "                HDvPop[t] = np.sum([ unitPop[u] for u in HDunitList[t] ])\n",
    "                nPatchSuccess +=1\n",
    "                #print(\"we added\",addSet,\"and shed units\",shedSet,\"from HD\",t)\n",
    "            else:\n",
    "                nPatchFail +=1\n",
    "        else:  #adding neither the UUU cluster or just the UUU worked; couldn't even start\n",
    "            nCouldntStart +=1\n",
    "            # end of shed + add patching on this HD\n",
    "            #print(\"shed and patched for HD, OUU\",t,OUU)\n",
    "\n",
    "    print(\"all done trying2increase usage of unit\",UUU,\"final usage =\",r5(unitUse[UUU]),int(time.time()-startTime),\"sec elapsed\",\n",
    "         nPatchSuccess,nPatchFail,\"complete, failed patches, unstarted=\",nCouldntStart)\n",
    "    currAvg, currSD = getWeightedAvgAndSD(unitUse,unitPop)\n",
    "    print(\"current avg and SD of usage are\",r5(currAvg), r5(currSD) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 137,
   "id": "c86e68bf-c3e5-4b21-a011-5e5144a7160e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "current avg and SD of usage are 1.00027 0.09304\n"
     ]
    }
   ],
   "source": [
    "currAvg, currSD = getWeightedAvgAndSD(unitUse,unitPop)\n",
    "print(\"current avg and SD of usage are\",r5(currAvg), r5(currSD) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "id": "1537f850-b59a-4706-a375-b5e863231af1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "save these semi-npatched results to temp file\n"
     ]
    }
   ],
   "source": [
    "print(\"save these semi-npatched results to temp file\")\n",
    "tList = [t for t in range(nHDs)]\n",
    "outDF = pd.DataFrame( {\"vtd\":tList,\"HDweight\":HDweight,\"HDvPop\":HDvPop,\"HDunitList\":HDunitList,\n",
    "                      \"splitUnitNo\":splitUnitNo,\"splitUnitFrac\":splitUnitFrac,\n",
    "                       \"centroid x\":HDCPx, \"centroid y\":HDCPy, \"homeU\":homeU, \"homeC\":homeC } )\n",
    "outname = STATE+str(int(nHDs))+\"_\"+str(nDistricts)+\"COI615_12hrPatch.csv\" #\"contigUnpatchedB.csv\" unpatchedContigGoodPop.csv\n",
    "outpath = \"2024state_HD_output/\"+outname\n",
    "outDF.to_csv(outpath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 144,
   "id": "c2a16dee-ffde-4304-a5a2-7b512679c3fa",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "reading in pre-patched so we can plot some comparisons\n",
      "I read in a total of 8941 home district unit lists, of which 8934 are populated\n"
     ]
    }
   ],
   "source": [
    "inDF = pd.read_csv(\"./2024state_HD_output/OH8941_15COI615goodPop.csv\")\n",
    "print(\"reading in pre-patched so we can plot some comparisons\")\n",
    "oldString = inDF[\"HDunitList\"]\n",
    "oldHDunitList = [ast.literal_eval(oldString[h]) for h in range(nHDs)]\n",
    "print(\"I read in a total of\",nHDs,\"home district unit lists, of which\",len(popHDlist),\"are populated\")\n",
    "oldHDvPop = inDF[\"HDvPop\"].to_numpy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "id": "2ca2820a-192b-4a00-bf0c-e8bb18c9f0e8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "we changed 553 HDs via the first patching pass\n"
     ]
    }
   ],
   "source": [
    "changedList = list()\n",
    "for t in popHDlist:\n",
    "    if len(oldHDunitList[t]) != len(HDunitList[t]) :\n",
    "        #print(t)\n",
    "        changedList.append(t)\n",
    "print(\"we changed\",len(changedList),\"HDs via the first patching pass\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 161,
   "id": "0f573ac2-94d1-481b-8188-e69939ca8017",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "t = changedList[480]\n",
    "plotPoly(HDCP[t].buffer(0.1))\n",
    "for u in oldHDunitList[t]:\n",
    "    if u in HDunitList[t]:\n",
    "        plotPoly(unitGeom[u].centroid.buffer(0.02))\n",
    "    else:\n",
    "        plotCenter(\"x\",unitGeom[u])\n",
    "for u in HDunitList[t]:\n",
    "    if u not in oldHDunitList[t]:\n",
    "        plotCenter(\"p\",unitGeom[u])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "id": "6f7f2f60-aa6c-4d46-b2e3-7d2f68841e68",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " patched use avg 1.00027 and SD 0.09304\n",
      "And here is the pop distro\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "checking contiguity of final HDs\n",
      "working on HD 0 out of 8941\n",
      "working on HD 800 out of 8941\n",
      "working on HD 1600 out of 8941\n",
      "working on HD 2400 out of 8941\n",
      "working on HD 3200 out of 8941\n",
      "working on HD 4000 out of 8941\n",
      "working on HD 4800 out of 8941\n",
      "working on HD 5600 out of 8941\n",
      "working on HD 6400 out of 8941\n",
      "working on HD 7200 out of 8941\n",
      "working on HD 8000 out of 8941\n",
      "working on HD 8800 out of 8941\n",
      "all done checking HD and complement contiguity for all 8941 HDs\n"
     ]
    }
   ],
   "source": [
    "patchedUse, unpUse = [0.]*nUnits, [0.]*nUnits\n",
    "for t in popHDlist:\n",
    "    if homeU[t] not in HDunitList[t]:\n",
    "        print(\"WARNING - we lost home unit\",homeU[t],\"from HD\",t)\n",
    "    for u in HDunitList[t]:\n",
    "        patchedUse[u] += HDweight[t] * nDistricts\n",
    "    if t in hasSplitUnit: #hasSplitUnit[t] == 1:\n",
    "        unitUse[splitUnitNo[t]] -= (1. - splitUnitFrac[t]) * nDistricts * HDweight[t]\n",
    "#    for u in unpatchedHDlist[t]:\n",
    "#        unpUse[u] += HDweight[t] * nDistricts\n",
    "plt.hist(patchedUse,bins=50, label=\"patched\",histtype=\"step\")\n",
    "#plt.hist(unpUse, bins=50, label=\"unpatched\",histtype=\"step\")\n",
    "plt.legend()\n",
    "plt.show()\n",
    "patchedAvg, patchedSD = getWeightedAvgAndSD(patchedUse,unitPop)\n",
    "#unpatchedAvg, unpatchedSD = getWeightedAvgAndSD(unpUse,unitPop)\n",
    "print(\" patched use avg\", r5(patchedAvg),\"and SD\",r5(patchedSD) )\n",
    "#print(\"unpatched, patched use avgs are\",r5(unpatchedAvg), r5(patchedAvg),\"and their SDs are\",r5(unpatchedSD), r5(patchedSD) )\n",
    "print(\"And here is the pop distro\")\n",
    "plt.hist([HDvPop[t] for t in popHDlist])\n",
    "plt.axvline(aDP, ls=\"--\",color=\"orange\")\n",
    "plt.axvline(0.95*aDP, ls=\"dotted\")\n",
    "plt.axvline(1.05*aDP, ls=\"dotted\")\n",
    "plt.show()\n",
    "print(\"checking contiguity of final HDs\")\n",
    "for t in popHDlist:\n",
    "    if t%800 == 0:\n",
    "        print(\"working on HD\",t,\"out of\",nHDs)\n",
    "    unbroken, noEnclave, sList, eList = enclaveCheck(HDunitList[t], unitNbrs)  #these HDunitLists now appear to be sets\n",
    "    if not unbroken or not noEnclave:\n",
    "        print(\"uh-oh, HD\",t,\"has contiguity, complement-contiguity of\",unbroken, noEnclave)\n",
    "print(\"all done checking HD and complement contiguity for all\",nHDs,\"HDs\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 163,
   "id": "6de20f70-be39-4abf-ae8b-61483239e04a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "unitUse by unitPop\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "underPatchedUnitList = [HDunitList[t].copy() for t in range(nHDs)] #safekeeping\n",
    "plt.scatter(unitPop,patchedUse,label=\"patched\")\n",
    "#plt.scatter(unitPop,unpatchedUnitUse,label=\"unpatched\")\n",
    "print(\"unitUse by unitPop\")\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a78054c8-3005-4c8b-835f-40e8056d2ee9",
   "metadata": {},
   "outputs": [],
   "source": [
    "#12/5/24 - stop here with patching, may come back later with split unit for the large u's w/use > 1.2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6302b395-2a3f-48cc-bc2d-f4ae984cf179",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 164,
   "id": "997b5c76-8331-48c3-ae0f-9bdd6bbfb34c",
   "metadata": {},
   "outputs": [],
   "source": [
    "HDunitList = [underPatchedUnitList[t].copy() for t in range(nHDs)] #restart\n",
    "unitUse, HDvPop = [0.]*nUnits, [0.]*nHDs\n",
    "for t in popHDlist:\n",
    "    if homeU[t] not in HDunitList[t]:\n",
    "        print(\"WARNING - we lost home unit\",homeU[t],\"from HD\",t)\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += HDweight[t] * nDistricts       \n",
    "        HDvPop[t] += unitPop[u]\n",
    "    if t in hasSplitUnit:\n",
    "        unitUse[splitUnitNo[t]] -= (1. - splitUnitFrac[t]) * nDistricts * HDweight[t]\n",
    "        HDvPop[t]               -= (1. - splitUnitFrac[t]) * unitPop[splitUnitNo[t]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 165,
   "id": "697ff263-82d5-4d4c-a50d-9730a859e6de",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "For now, we will disallow (freeze) HDs from patching.\n",
      "Try patching some more.  Still do not allow split units --- could change this later\n",
      "Currently, we will stop patching when the overall sd of usage is less than 0.075\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter updated maxSD value 0.075\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "this would currently cover a total of 949 units\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter updated number of units to try boosting usage 200\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "there are currently 1805 units out of 3099 with usage below 0.98\n",
      "maxExchangePop is currently 0.15 fraction of avgDistrictPop\n",
      "Let's further tighten the distro with exchanges up to 117994 = aDP* 0.15\n",
      "current avg and SD of unit usage are 1.00027 0.09304 . Now trying to increase up to 200 units' underusage\n",
      "try to add unit 1135 from 0 th HD.  Usage up to 0.7231901865238282\n",
      "try to add unit 1135 from 100 th HD.  Usage up to 0.7279281200271571\n",
      "try to add unit 1135 from 200 th HD.  Usage up to 0.7373391534924497\n",
      "try to add unit 1135 from 300 th HD.  Usage up to 0.7670125755033724\n",
      "try to add unit 1135 from 400 th HD.  Usage up to 0.7978428312916032\n",
      "try to add unit 1135 from 500 th HD.  Usage up to 0.8291917554107594\n",
      "try to add unit 1135 from 600 th HD.  Usage up to 0.887126245227553\n",
      "try to add unit 1135 from 700 th HD.  Usage up to 0.9580312570552063\n",
      "all done trying2increase usage of unit 1135 final usage = 0.96307 9402 sec elapsed 136 506 complete, failed patches, unstarted= 65\n",
      "current avg and SD of usage are 1.00032 0.09174\n",
      "try to add unit 235 from 0 th HD.  Usage up to 0.7273954679912085\n",
      "try to add unit 235 from 100 th HD.  Usage up to 0.7475091207654689\n",
      "all done trying2increase usage of unit 235 final usage = 0.82331 9944 sec elapsed 59 33 complete, failed patches, unstarted= 96\n",
      "current avg and SD of usage are 1.00033 0.09027\n",
      "try to add unit 211 from 0 th HD.  Usage up to 0.7320583979858982\n",
      "try to add unit 211 from 100 th HD.  Usage up to 0.7708021595584672\n",
      "all done trying2increase usage of unit 211 final usage = 0.8296 10791 sec elapsed 61 71 complete, failed patches, unstarted= 6\n",
      "current avg and SD of usage are 1.00034 0.08916\n",
      "try to add unit 3052 from 0 th HD.  Usage up to 0.7466840821704589\n",
      "try to add unit 3052 from 100 th HD.  Usage up to 0.7549242981534404\n",
      "try to add unit 3052 from 200 th HD.  Usage up to 0.756801928361226\n",
      "try to add unit 3052 from 300 th HD.  Usage up to 0.76173563373456\n",
      "try to add unit 3052 from 400 th HD.  Usage up to 0.7667824799938066\n",
      "try to add unit 3052 from 500 th HD.  Usage up to 0.7696783781748057\n",
      "try to add unit 3052 from 600 th HD.  Usage up to 0.7720543367789708\n",
      "try to add unit 3052 from 700 th HD.  Usage up to 0.7720543367789708\n",
      "try to add unit 3052 from 800 th HD.  Usage up to 0.7720543367789708\n",
      "try to add unit 3052 from 900 th HD.  Usage up to 0.7739281532490293\n",
      "try to add unit 3052 from 1000 th HD.  Usage up to 0.7784003963573498\n",
      "try to add unit 3052 from 1100 th HD.  Usage up to 0.7784003963573498\n",
      "try to add unit 3052 from 1200 th HD.  Usage up to 0.7817971654265453\n",
      "try to add unit 3052 from 1300 th HD.  Usage up to 0.7838654825207001\n",
      "try to add unit 3052 from 1400 th HD.  Usage up to 0.7849765514452803\n",
      "try to add unit 3052 from 1500 th HD.  Usage up to 0.7918883154532222\n",
      "try to add unit 3052 from 1600 th HD.  Usage up to 0.7952126235055981\n",
      "try to add unit 3052 from 1700 th HD.  Usage up to 0.8005582125534911\n",
      "all done trying2increase usage of unit 3052 final usage = 0.80056 14972 sec elapsed 31 395 complete, failed patches, unstarted= 1347\n",
      "current avg and SD of usage are 1.00034 0.08833\n",
      "try to add unit 2361 from 0 th HD.  Usage up to 0.7497833796968738\n",
      "try to add unit 2361 from 100 th HD.  Usage up to 0.7527746213210569\n",
      "try to add unit 2361 from 200 th HD.  Usage up to 0.760960173729947\n",
      "try to add unit 2361 from 300 th HD.  Usage up to 0.769938983586132\n",
      "try to add unit 2361 from 400 th HD.  Usage up to 0.7774685731059104\n",
      "try to add unit 2361 from 500 th HD.  Usage up to 0.7852015619711494\n",
      "try to add unit 2361 from 600 th HD.  Usage up to 0.7852015619711494\n",
      "try to add unit 2361 from 700 th HD.  Usage up to 0.793802811792325\n",
      "try to add unit 2361 from 800 th HD.  Usage up to 0.8018192884953015\n",
      "try to add unit 2361 from 900 th HD.  Usage up to 0.8077293107268483\n",
      "try to add unit 2361 from 1000 th HD.  Usage up to 0.8077293107268483\n",
      "try to add unit 2361 from 1100 th HD.  Usage up to 0.8140168929934052\n",
      "try to add unit 2361 from 1200 th HD.  Usage up to 0.8178674968521611\n",
      "try to add unit 2361 from 1300 th HD.  Usage up to 0.8178674968521611\n",
      "try to add unit 2361 from 1400 th HD.  Usage up to 0.8269988562174431\n",
      "try to add unit 2361 from 1500 th HD.  Usage up to 0.8319351040825946\n",
      "try to add unit 2361 from 1600 th HD.  Usage up to 0.8336449298303741\n",
      "try to add unit 2361 from 1700 th HD.  Usage up to 0.8346352303935869\n",
      "try to add unit 2361 from 1800 th HD.  Usage up to 0.8438276095625095\n",
      "all done trying2increase usage of unit 2361 final usage = 0.84542 21381 sec elapsed 55 545 complete, failed patches, unstarted= 1264\n",
      "current avg and SD of usage are 1.00034 0.08767\n",
      "try to add unit 533 from 0 th HD.  Usage up to 0.7513304859683034\n",
      "try to add unit 533 from 100 th HD.  Usage up to 0.8344407297695196\n",
      "all done trying2increase usage of unit 533 final usage = 0.85108 21600 sec elapsed 68 5 complete, failed patches, unstarted= 40\n",
      "current avg and SD of usage are 1.00035 0.08682\n",
      "try to add unit 1261 from 0 th HD.  Usage up to 0.7531877762415934\n",
      "all done trying2increase usage of unit 1261 final usage = 0.75807 22004 sec elapsed 3 19 complete, failed patches, unstarted= 25\n",
      "current avg and SD of usage are 1.00035 0.0868\n",
      "try to add unit 1140 from 0 th HD.  Usage up to 0.7575214535457884\n",
      "try to add unit 1140 from 100 th HD.  Usage up to 0.7575214535457884\n",
      "try to add unit 1140 from 200 th HD.  Usage up to 0.7575214535457884\n",
      "try to add unit 1140 from 300 th HD.  Usage up to 0.7595529045085784\n",
      "try to add unit 1140 from 400 th HD.  Usage up to 0.7632446026286938\n",
      "try to add unit 1140 from 500 th HD.  Usage up to 0.7649734970651113\n",
      "try to add unit 1140 from 600 th HD.  Usage up to 0.7735544069517408\n",
      "try to add unit 1140 from 700 th HD.  Usage up to 0.7735544069517408\n",
      "try to add unit 1140 from 800 th HD.  Usage up to 0.7776312925823208\n",
      "try to add unit 1140 from 900 th HD.  Usage up to 0.779063986721911\n",
      "try to add unit 1140 from 1000 th HD.  Usage up to 0.781584867359716\n",
      "try to add unit 1140 from 1100 th HD.  Usage up to 0.781584867359716\n",
      "try to add unit 1140 from 1200 th HD.  Usage up to 0.7830722250733989\n",
      "try to add unit 1140 from 1300 th HD.  Usage up to 0.7830722250733989\n",
      "try to add unit 1140 from 1400 th HD.  Usage up to 0.7830722250733989\n",
      "try to add unit 1140 from 1500 th HD.  Usage up to 0.7830722250733989\n",
      "try to add unit 1140 from 1600 th HD.  Usage up to 0.7830722250733989\n",
      "try to add unit 1140 from 1700 th HD.  Usage up to 0.7830722250733989\n",
      "try to add unit 1140 from 1800 th HD.  Usage up to 0.7830722250733989\n",
      "all done trying2increase usage of unit 1140 final usage = 0.78307 28074 sec elapsed 14 496 complete, failed patches, unstarted= 1292\n",
      "current avg and SD of usage are 1.00035 0.08671\n",
      "try to add unit 878 from 0 th HD.  Usage up to 0.760576257465458\n",
      "try to add unit 878 from 100 th HD.  Usage up to 0.760576257465458\n",
      "try to add unit 878 from 200 th HD.  Usage up to 0.7813268044401921\n",
      "all done trying2increase usage of unit 878 final usage = 0.78133 30877 sec elapsed 8 194 complete, failed patches, unstarted= 1\n",
      "current avg and SD of usage are 1.00035 0.08659\n",
      "begin usage increase for unit 1262 with usage 0.76248 . Sec, total UU units tried = 30878 10\n",
      "try to add unit 1262 from 0 th HD.  Usage up to 0.7624831263291543\n",
      "all done trying2increase usage of unit 1262 final usage = 0.76377 31175 sec elapsed 1 16 complete, failed patches, unstarted= 26\n",
      "current avg and SD of usage are 1.00035 0.08658\n",
      "try to add unit 1144 from 0 th HD.  Usage up to 0.7650929941805722\n",
      "try to add unit 1144 from 100 th HD.  Usage up to 0.7650929941805722\n",
      "try to add unit 1144 from 200 th HD.  Usage up to 0.7650929941805722\n",
      "try to add unit 1144 from 300 th HD.  Usage up to 0.7681961054447596\n",
      "try to add unit 1144 from 400 th HD.  Usage up to 0.7681961054447596\n",
      "try to add unit 1144 from 500 th HD.  Usage up to 0.7681961054447596\n",
      "try to add unit 1144 from 600 th HD.  Usage up to 0.7728806466199051\n",
      "try to add unit 1144 from 700 th HD.  Usage up to 0.7752006704040676\n"
     ]
    },
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "Cell \u001b[1;32mIn[165], line 98\u001b[0m\n\u001b[0;32m     96\u001b[0m listNo \u001b[38;5;241m=\u001b[39m idx[ij]   \u001b[38;5;66;03m#work from low to high score\u001b[39;00m\n\u001b[0;32m     97\u001b[0m addU \u001b[38;5;241m=\u001b[39m addCandidates[listNo]\n\u001b[1;32m---> 98\u001b[0m cContig \u001b[38;5;241m=\u001b[39m \u001b[43mwontEnclave\u001b[49m\u001b[43m(\u001b[49m\u001b[43maddU\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mlist\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mtrySet\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43munitNbrs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mborderUnits\u001b[49m\u001b[43m)\u001b[49m  \u001b[38;5;66;03m#4/20/24 sub this in as faster? vs below line\u001b[39;00m\n\u001b[0;32m     99\u001b[0m \u001b[38;5;66;03m#contig,cContig, __, ___ = enclaveCheck(list(trySet.union({addU}) ), unitNbrs)  #4/20/24 this is unnec slow\u001b[39;00m\n\u001b[0;32m    100\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m cContig: \u001b[38;5;66;03m#contig and cContig:\u001b[39;00m\n",
      "Cell \u001b[1;32mIn[1], line 205\u001b[0m, in \u001b[0;36mwontEnclave\u001b[1;34m(proposedU, dList, NBRLIST, mapBDRYLIST)\u001b[0m\n\u001b[0;32m    203\u001b[0m                 adjSet \u001b[38;5;241m=\u001b[39m adjSet\u001b[38;5;241m.\u001b[39munion( \u001b[38;5;28mset\u001b[39m(NBRLIST[UU])\u001b[38;5;241m.\u001b[39mdifference(\u001b[38;5;28mset\u001b[39m(newList)) )\n\u001b[0;32m    204\u001b[0m             ADJLIST \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mlist\u001b[39m(adjSet)\n\u001b[1;32m--> 205\u001b[0m             wontEnclave, __ \u001b[38;5;241m=\u001b[39m   \u001b[43misContiguous\u001b[49m\u001b[43m(\u001b[49m\u001b[43mADJLIST\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mNBRLIST\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    207\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m wontEnclave\n",
      "Cell \u001b[1;32mIn[1], line 84\u001b[0m, in \u001b[0;36misContiguous\u001b[1;34m(VLIST, NEIGHBORLIST, returnBiggestPiece)\u001b[0m\n\u001b[0;32m     82\u001b[0m             \u001b[38;5;28;01mif\u001b[39;00m VV \u001b[38;5;129;01min\u001b[39;00m VLIST \u001b[38;5;129;01mand\u001b[39;00m VV \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;129;01min\u001b[39;00m foundList:\n\u001b[0;32m     83\u001b[0m                 newList\u001b[38;5;241m.\u001b[39mappend(VV)\n\u001b[1;32m---> 84\u001b[0m                 \u001b[43mfoundList\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mappend\u001b[49m\u001b[43m(\u001b[49m\u001b[43mVV\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m     85\u001b[0m     prevList \u001b[38;5;241m=\u001b[39m newList\u001b[38;5;241m.\u001b[39mcopy()      \n\u001b[0;32m     86\u001b[0m pickedPieceList \u001b[38;5;241m=\u001b[39m foundList\u001b[38;5;241m.\u001b[39mcopy()  \u001b[38;5;66;03m#default contiguous sublist to pass back to main\u001b[39;00m\n",
      "\u001b[1;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],
   "source": [
    "print(\"For now, we will disallow (freeze) HDs from patching.\")\n",
    "print(\"Try patching some more.  Still do not allow split units --- could change this later\")\n",
    "\n",
    "maxSD = 0.075  #0.055   #adjust down if distro already tight\n",
    "print(\"Currently, we will stop patching when the overall sd of usage is less than\",maxSD)\n",
    "maxSD = float(input(\"enter updated maxSD value\"))\n",
    "stopMinUse = 1. - maxSD\n",
    "#print(\"we will stop patching on individual underused units when their usage exceeds\",r5(stopMinUse))\n",
    "maxNtries = 0\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] < stopMinUse:\n",
    "        maxNtries +=1\n",
    "print(\"this would currently cover a total of\",maxNtries,\"units\")\n",
    "maxNtries = int(input(\"enter updated number of units to try boosting usage\"))\n",
    "stopMinUse = 0.98 #float(input(\"enter updated stopMinUse value for ending usage boost on a unit; I reco 0.98\"))\n",
    "nInPlay = 0\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] < stopMinUse:\n",
    "        nInPlay +=1\n",
    "print(\"there are currently\",nInPlay,\"units out of\",nUnits,\"with usage below\",stopMinUse)\n",
    "maxExchangePop = 0.15*aDP #this is widened vs. vanillaHD to overcome blockiness\n",
    "print(\"maxExchangePop is currently\",r5(maxExchangePop/aDP),\"fraction of avgDistrictPop\")\n",
    "debug1 = 10 #int(input(\"enter 1 to print out stats for every patched HD, otherwise enter reporting frequency\"))\n",
    "print(\"Let's further tighten the distro with exchanges up to\",int(maxExchangePop),\"= aDP*\",r3(maxExchangePop/aDP) ) \n",
    "maxGap = aDP - minDistrictPop  #0.9 * np.median(unitPop)   #aDP - minDistrictPop  \n",
    "currAvg, currSD = getWeightedAvgAndSD(unitUse,unitPop)\n",
    "nonfrozenList = list(  set(popHDlist).difference( set(hasSplitUnit) )  )\n",
    "\n",
    "attemptedSmallUs, startTime = list(), time.time()\n",
    "print(\"current avg and SD of unit usage are\",r5(currAvg), r5(currSD),\". Now trying to increase up to\",maxNtries,\"units' underusage\" )\n",
    "startTime = time.time()\n",
    "while currSD > maxSD and len(attemptedSmallUs) < maxNtries:\n",
    "    #simplified vs. vanillaHD - always work on the lowest-used unit.\n",
    "    eligUnitUse = unitUse.copy()\n",
    "    for u in range(nUnits):\n",
    "        if u in attemptedSmallUs: #we already tried this one, so lock it out\n",
    "            eligUnitUse[u] = 999.  #preventing re-selection\n",
    "    UUU = eligUnitUse.index(np.min(eligUnitUse))\n",
    "    attemptedSmallUs.append(UUU)\n",
    "    UUUc = [UUU] + unitNbrs[UUU]\n",
    "    if len(attemptedSmallUs) % debug1 == 0:\n",
    "        print(\"begin usage increase for unit\",UUU,\"with usage\",r5(unitUse[UUU]),\". Sec, total UU units tried =\",\n",
    "              int(time.time()-startTime),len(attemptedSmallUs) )\n",
    "    for u in UUUc.copy():\n",
    "        if unitUse[u] > 1.:\n",
    "            UUUc.remove(u)  #...drop any overused neighbors of the primary UUU from the target sheddable cluster\n",
    "    uuuHDs, uuuDists, UUUcSet = list(), list(), set(UUUc)\n",
    "    for t in nonfrozenList: #popHDlist:  #finding all HDs with at least one cluster member on the boundary\n",
    "        if UUU not in HDunitList[t]:\n",
    "            HDadjoinSet = set( getAdjoiners(HDunitList[t],unitNbrs) )\n",
    "            if len(HDadjoinSet.intersection(UUUcSet) ) > 0: #the UUU or one of its underused 1-neighbors adjoins this HD\n",
    "                uuuHDs.append(t)  #Note: we'll check later if we can contiguously pick up the UUU's cluster\n",
    "                uuuDists.append( unitCP[UUU].distance(hdCP[t]) / avgDist[t] )\n",
    "        idx0 = np.argsort(uuuDists)\n",
    "    hasCandidates = True\n",
    "    if len(uuuDists) == 0:  #this underused unit is buried inside others; skip it\n",
    "        hasCandidates = False\n",
    "        print(\"   Couldn't find any HDs adjacent to underused unit\",UUU)\n",
    "    nPatchSuccess, nPatchFail, nCouldntStart, idxNo = 0,0,0,-1\n",
    "    while unitUse[UUU] < stopMinUse and idxNo < 0.8*len(uuuHDs) and hasCandidates: #arbitrarily only examine 80% closest of HDs\n",
    "        excess, giveUpOnShedding = 99*aDP, True  #default = failed swap\n",
    "        idxNo += 1\n",
    "        if idxNo % 100 == 0 : #and debug1 == 1:\n",
    "            print(\"try to add unit\",UUU,\"from\",abs(idxNo),\"th HD.  Usage up to\",unitUse[UUU] )\n",
    "        t = uuuHDs[idx0[idxNo]]\n",
    "        trySet = set(HDunitList[t]).union(UUUcSet)\n",
    "        tryPop = np.sum([unitPop[u] for u in trySet])\n",
    "        contig,complementContig, __, ___ = enclaveCheck(list(trySet), unitNbrs)\n",
    "        loopUUUc = UUUc.copy()  #default; we will add whole cluster\n",
    "        if not (contig and complementContig and tryPop < aDP + maxExchangePop): \n",
    "            #we can't add whole cluster; neighbors may be enclavy or too much pop.   Try just adding the UUU\n",
    "            trySet = set(HDunitList[t]).union({UUU})\n",
    "            contig,complementContig, __, ___ = enclaveCheck(list(trySet), unitNbrs)\n",
    "            loopUUUc = [UUU]\n",
    "        if contig and complementContig:  #we can at least add the cluster, let's go for more\n",
    "            HDuuuSet = set(loopUUUc).difference(set(HDunitList[t]))  #the subset of the UUU cluster that adjoins (NOT in) this HD\n",
    "            HDuuuCpop = np.sum([unitPop[u] for u in HDuuuSet])\n",
    "            giveUpOnAdding = False            \n",
    "            addCandidates, addUseDists = list(), list()\n",
    "            uuCandidates = getAdjoiners(trySet, unitNbrs)  #any adjoiner can be picked up, even if far from UUUc\n",
    "            for u in uuCandidates:\n",
    "                if HDuuuCpop + unitPop[u] <= maxExchangePop:\n",
    "                    addCandidates.append(u)  #Below's relative scoring of use and distance is a bit arbitrary\n",
    "                    addUseDists.append((unitUse[uu]-1.) + 0.1*unitCP[uu].distance(hdCP[t]) / avgDist[t])  #bias toward close, underused\n",
    "            if len(addCandidates) == 0:\n",
    "                giveUpOnAdding = True\n",
    "            while HDuuuCpop < maxExchangePop and not giveUpOnAdding:\n",
    "                addNneighbors = [len( set(unitNbrs[addC]).intersection(trySet) ) for addC in addCandidates ]\n",
    "                addScores = addUseDists.copy()\n",
    "                for jjj, u in enumerate(addCandidates):\n",
    "                    if addNneighbors[jjj] == 1:\n",
    "                        addScores[jjj] += 0.4321    #discourage growing fingers\n",
    "                #print(\"HDuuuCpop is now\",HDuuuCpop)\n",
    "                idx, ij, notYetPicked = np.argsort(addScores), 0, True\n",
    "                while ij < 0.5*len(addScores) and notYetPicked:\n",
    "                    listNo = idx[ij]   #work from low to high score\n",
    "                    addU = addCandidates[listNo]\n",
    "                    cContig = wontEnclave(addU, list(trySet), unitNbrs, borderUnits)  #4/20/24 sub this in as faster? vs below line\n",
    "                    #contig,cContig, __, ___ = enclaveCheck(list(trySet.union({addU}) ), unitNbrs)  #4/20/24 this is unnec slow\n",
    "                    if cContig: #contig and cContig:\n",
    "                        notYetPicked = False\n",
    "                        HDuuuCpop += unitPop[addU]\n",
    "                        HDuuuSet.add(addU)\n",
    "                        trySet.add(addU)\n",
    "                        del addUseDists[addCandidates.index(addU)]\n",
    "                        del addCandidates[addCandidates.index(addU)]                        \n",
    "                        for uu in list(set(unitNbrs[addU]).difference(trySet) ): \n",
    "                            if uu not in addCandidates and unitPop[uu] + HDuuuCpop < maxExchangePop and unitUse[uu] < 1.01:\n",
    "                                addCandidates.append(uu)\n",
    "                                addUseDists.append( (unitUse[uu]-1.) + 0.1*unitCP[uu].distance(hdCP[t]) / avgDist[t] )\n",
    "                    else:\n",
    "                        ij +=1\n",
    "                if notYetPicked:\n",
    "                    giveUpOnAdding = True  #all candidates would create a discontig, so can't shed any more units\n",
    "            addSet = HDuuuSet.copy()  #we're done building the list of underused units to add to this HD\n",
    "            trySet = set(HDunitList[t]).union(addSet) \n",
    "            excess = np.sum([unitPop[u] for u in trySet]) - aDP\n",
    "            shedCandidates, shedScores, giveUpOnShedding = list(), list(), False\n",
    "            bdryCandidates = getBdryNonEdgers(trySet, unitNbrs)  #new - any boundary unit can be shed, even if far from OUUc\n",
    "            for u in bdryCandidates:\n",
    "                if unitPop[u] <= excess + maxGap and u != homeU[t]:\n",
    "                    shedCandidates.append(u)\n",
    "                    shedScores.append((unitUse[u] - 1.) * unitCP[u].distance(hdCP[t])/avgDist[t])  #bias toward OVERUSED, far\n",
    "            if len(shedCandidates) == 0:\n",
    "                giveUpOnShedding = True\n",
    "            shedSet = set()\n",
    "            while excess > maxGap and not giveUpOnShedding:\n",
    "                #print(\"excess pop is now\",excess,\"for HD\",t)\n",
    "                idx, ij, notYetPicked = np.argsort(shedScores), 0, True\n",
    "                while ij < len(shedScores) and notYetPicked:\n",
    "                    listNo = idx[-1-ij]   #work from high to low score\n",
    "                    shedU = shedCandidates[listNo]\n",
    "                    if shedScores[listNo] <= 0:  #we're delving into the underused; stop adding to shed list\n",
    "                        break\n",
    "                    if excess - unitPop[shedU] >= -1*maxGap:\n",
    "                        contig,cContig, __, ___ = enclaveCheck(list(trySet.difference({shedU}) ), unitNbrs)\n",
    "                        if contig and cContig:\n",
    "                            notYetPicked = False\n",
    "                            excess -= unitPop[shedU]\n",
    "                            trySet.remove(shedU)\n",
    "                            shedSet.add(shedU)\n",
    "                            del shedScores[shedCandidates.index(shedU)]\n",
    "                            del shedCandidates[shedCandidates.index(shedU)]\n",
    "                            newSheddables = set(unitNbrs[shedU]).intersection(trySet)\n",
    "                            for u in newSheddables:\n",
    "                                if excess - unitPop[u] >= -1*maxGap and u not in shedCandidates + [homeU[t]]:\n",
    "                                    shedCandidates.append(u)  #we'll check enclavity if ever picked\n",
    "                                    shedScores.append((unitUse[u] - 1.) * unitCP[u].distance(hdCP[t])/avgDist[t])\n",
    "                            for kkk, u in enumerate(shedCandidates): #checking if this shed eliminates high-pop future sheds ...\n",
    "                                if excess - unitPop[u] < -1*maxGap:\n",
    "                                    del shedScores[kkk]\n",
    "                                    del shedCandidates[kkk]\n",
    "                    ij +=1\n",
    "                if notYetPicked:\n",
    "                    giveUpOnShedding = True  #all shedcandidates would create a discontig, so can't shed enough units to square pop\n",
    "            legitSwap = False\n",
    "            currPop = np.sum([ unitPop[u] for u in trySet] )\n",
    "            if abs(currPop - aDP) <= maxGap: \n",
    "                contig,cContig, __, ___ = enclaveCheck(list(trySet), unitNbrs) \n",
    "                if contig and cContig:\n",
    "                    legitSwap = True\n",
    "            if legitSwap:\n",
    "                for u in shedSet:\n",
    "                    unitUse[u] -= HDweight[t] * nDistricts\n",
    "                for u in addSet:\n",
    "                    unitUse[u] += HDweight[t] * nDistricts\n",
    "                HDunitList[t] = list(trySet)\n",
    "                HDvPop[t] = np.sum([ unitPop[u] for u in HDunitList[t] ])\n",
    "                nPatchSuccess +=1\n",
    "                #print(\"we added\",addSet,\"and shed units\",shedSet,\"from HD\",t)\n",
    "            else:\n",
    "                nPatchFail +=1\n",
    "        else:  #adding neither the UUU cluster or just the UUU worked; couldn't even start\n",
    "            nCouldntStart +=1\n",
    "            # end of shed + add patching on this HD\n",
    "            #print(\"shed and patched for HD, OUU\",t,OUU)\n",
    "\n",
    "    print(\"all done trying2increase usage of unit\",UUU,\"final usage =\",r5(unitUse[UUU]),int(time.time()-startTime),\"sec elapsed\",\n",
    "         nPatchSuccess,nPatchFail,\"complete, failed patches, unstarted=\",nCouldntStart)\n",
    "    currAvg, currSD = getWeightedAvgAndSD(unitUse,unitPop)\n",
    "    print(\"current avg and SD of usage are\",r5(currAvg), r5(currSD) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 166,
   "id": "aee0c9e2-e1f3-4728-99d1-32cd8f56d8ab",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " patched use avg 1.00036 and SD 0.08652\n",
      "And here is the pop distro\n"
     ]
    },
    {
     "data": {
      "image/png": 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1qsaNG6cvvvhCfr9f48aN07x587R27Vrrta666ipVV1dr/vz5jYqN06iBZiq0V5rVUpLUfc0LqjWpkjiNGmguYnIadU1NjSQpOztbkrRq1SoFg0ENGjTI6tOtWze1b99e5eXlkqTy8nL16tXLKl4kqaioSIFAQOvWrbP6fPsYB/ocOMah1NfXKxAIRN2amjFG+xpC2tcQUjO9fA4AAN/LLbnwiAuYSCSi2267TWeeeaZOOukkSVJlZaX8fr+ysrKi+ubm5qqystLq8+3i5cDzB577vj6BQEC1tbWHjKe0tFSZmZnWraCg4EiHdli1wbB63L1APe5eoNogZyEBABKPW3LhERcwJSUlWrt2rWbOnNmU8RyxCRMmqKamxrp9+umnTocEAACOkiPagWn06NGaO3euli5dqnbt2lmP5+XlqaGhQdXV1VGzMFVVVcrLy7P6rFy5Mup4B85S+naf7565VFVVpYyMDKWlpR0yppSUFKWkpBzJcBotLdmn9fcVWW0ADvClS1fsUfe75qvWHN3PPICDuSUX2pqBMcZo9OjRevnll7V48WJ16tQp6vm+ffsqOTlZixYtsh7btGmTtm/frsLCQklSYWGh1qxZo127dll9ysrKlJGRoR49elh9vn2MA30OHMMpHo9H6f4kpfuTHNs+HEh4Ho+U1OJ/Fu/yOQRizS250NYMTElJiWbMmKFXXnlFxxxzjLVmJTMzU2lpacrMzNSoUaM0ZswYZWdnKyMjQ7/61a9UWFioAQMGSJIGDx6sHj16aMSIEZo8ebIqKys1ceJElZSUWDMoN998s/785z/rzjvv1PXXX6/Fixdr1qxZmjdv3mFjAwAAicPWadSHq7SmTZuma6+9VtL+C9n9+te/1nPPPaf6+noVFRXpiSeesL4ekqRPPvlEt9xyi5YsWaIWLVpo5MiRevDBB5WU9L/11JIlS3T77bdr/fr1ateune666y7rNRrjaJxG3RCK6LFFH0mSbj3vBK4FAzghXC+tvEkvrPpMv/l8tBpMsiROowZi5Wjnwsbm7x91HRg3OxoFzL6GkHrcvf9ieuvvK1K6/4iWEAH4MbgODOCoo50LG5u/ycA2+LweXXdmR6sNAECicUsupICxISXJp3t+1tPpMAAAcIxbciGLOAAAQNyhgAEAAHGHAsaGfQ0hdRw/Tx3Hz9O+hpDT4QAAEHNuyYUUMAAAIO6wiNeGtGSfVk0cZLUBOMCXLl22S6feX8ZWAoAD3JILKWBs8Hg8atWSfzABR3k8Umob7Q5nOh0JkJDckgspYAC4XsfxbCMCIBoFjA0NoYj+unSrJOnGgV3YSgBwgN8T1MS2f5ck/W7nL6ytBADEhltyIQWMDaFIRA+/vn//h+vP6iQ/a6CBmPMprGta75+RKd15nSQKGCCW3JILKWBs8Hk9uur0AqsNAECicUsupICxISXJpweH9nY6DAAAHOOWXMh3IAAAIO5QwAAAgLhDAWPDvoaQut81X93vms9WAgCAhOSWXMgaGJtqg2GnQwAAwFFuyIUUMDakJvn01p3nWm0AsVdn/Dprwz+sNoDYcksupICxwev1qCA73ekwgIRm5NVnwVynwwASlltyIWtgAABA3GEGxoZgOKKnyz+RJF1T2EHJPuo/INaSPUHdkfeMJOnhyhEKspUAEFNuyYUUMDYEwxHdP3e9JGlYvwIKGMABSQrrpjYvSZIerbxaQbYSAGLKLbmQAsYGr8ejS/rkW20AABKNW3IhBYwNqck+PXbVKU6HAQCAY9ySC/kOBAAAxB0KGAAAEHcoYGzY1xDSqfeX6dT7y9hKAACQkNySC1kDY9PuvQ1OhwAAgKPckAspYGxITfLp9dsHWm0AsVdn/Dp/0xSrDSC23JILKWBs8Ho9OiH3GKfDABKakVeb6zs4HQaQsNySC1kDAwAA4g4zMDYEwxG9sOozSdLlfdtxJV7AAcmeoEpyZkmSpuy6gq0EgBhzSy6kgLEhGI5owktrJEmX9MmngAEckKSwbst9TpL0l11D2UoAiDG35EIKGBu8Ho/O75FrtQEASDRuyYUUMDakJvv0t2tOczoMAAAc45ZcyHcgAAAg7jADA6BZ6Dh+3kGPffxgsQORAIgFZmBsqG0I68wHF+vMBxertiHsdDgAAMScW3IhMzA2GBl9Xl1rtQEASDRuyYUUMDakJPn0SsmZVhtA7NWbZF28+Y9WG0BsuSUXUsDY4PN6dHJBltNhAAktIp9W157gdBhAwnJLLmQNDAAAiDvMwNgQCkc0d/VOSdJFvdsqiSvxAjGX7Anqutb/kiRN+/JithIAYswtuZACxoaGcES3PV8hSRrcM5cCBnBAksL6TdtpkqRnvixmKwEgxtySCylgbPB6PDqra2urDQBAonFLLqSAsSE12af//kV/p8MAAMAxbsmFfAcCAADiDgUMAACIOxQwNtQ2hHX+H9/U+X98k60EAAAJyS25kDUwNhgZbd61x2oDAJBo3JILKWBsSEny6bkbBlhtALFXb5J11dYHrDaA2HJLLqSAscHn9aiwSyunwwASWkQ+Ld/b2+kwgITlllzIGhgAABB3bBcwS5cu1c9+9jPl5+fL4/Fozpw5Uc9fe+218ng8UbcLLrggqs/u3bs1fPhwZWRkKCsrS6NGjdKePXui+qxevVpnn322UlNTVVBQoMmTJ9sfXRMLhSNasK5SC9ZVKhSOOB0OkJCSFNKIVnM1otVcJSnkdDhAwnFLLrRdwOzdu1cnn3yypkyZctg+F1xwgXbu3Gndnnvuuajnhw8frnXr1qmsrExz587V0qVLdeONN1rPBwIBDR48WB06dNCqVav00EMPadKkSfrrX/9qN9wm1RCO6KZnVummZ1apgQIGcESyJ6T7j5uq+4+bqmQPBQwQa27JhbbXwAwZMkRDhgz53j4pKSnKy8s75HMbNmzQ/Pnz9e677+q0006TJP3pT3/ShRdeqIcfflj5+fl69tln1dDQoKeeekp+v189e/ZURUWF/vjHP0YVOrHm9XjUt8OxVhsAgETjllx4VNbALFmyRDk5OTrxxBN1yy236KuvvrKeKy8vV1ZWllW8SNKgQYPk9Xq1YsUKq8/AgQPl9/utPkVFRdq0aZO+/vrrQ75mfX29AoFA1K2ppSb79OItZ+jFW85QajJnIQEAEo9bcmGTFzAXXHCBnn76aS1atEj/7//9P7355psaMmSIwuH9F7uprKxUTk5O1M8kJSUpOztblZWVVp/c3NyoPgfuH+jzXaWlpcrMzLRuBQUFTT00AADgEk1+GvVVV11ltXv16qXevXurS5cuWrJkic4777ymfjnLhAkTNGbMGOt+IBCgiAEAoJk66qdRd+7cWa1bt9aWLVskSXl5edq1a1dUn1AopN27d1vrZvLy8lRVVRXV58D9w62tSUlJUUZGRtStqdUFw7r4z8t08Z+XqS7IVgIAgMTjllx41AuYzz77TF999ZXatm0rSSosLFR1dbVWrVpl9Vm8eLEikYj69+9v9Vm6dKmCwaDVp6ysTCeeeKKOPfbYox3yYUWM0erParT6sxpFDFsJAAASj1tyoe2vkPbs2WPNpkjStm3bVFFRoezsbGVnZ+vee+/V0KFDlZeXp61bt+rOO+9U165dVVRUJEnq3r27LrjgAt1www2aOnWqgsGgRo8erauuukr5+fmSpKuvvlr33nuvRo0apXHjxmnt2rV67LHH9MgjjzTRsI+M3+fVU9eeZrUBxF6DSdZ12+6x2gBiyy250GOMvfJpyZIlOvfccw96fOTIkXryySd16aWX6oMPPlB1dbXy8/M1ePBg3X///VGLcnfv3q3Ro0fr3//+t7xer4YOHarHH39cLVu2tPqsXr1aJSUlevfdd9W6dWv96le/0rhx4xodZyAQUGZmpmpqao7K10kAYqfj+HlH9HMfP1jcxJEAONoam79tFzDxggIGaD4oYIDE0dj8zWaONoQjRu9s/VKSdEaX1vJ5uZgdEGtJCunSY5dIkuZ8fY5C/DMGxJRbciGffBvqQ2GN+MdKSdL6+4qU7ufXB8RasiekhwselSTNqz5LIcPnEIglt+RCPvk2eD0edW+bYbUBAEg0bsmFFDA2pCb79NqtZzsdBgAAjnFLLuRcYAAAEHcoYAAAQNyhgLGhLhjWlX8p15V/KWcrAQBAQnJLLmQNjA0RY7Ri226rDQBAonFLLqSAscHv82rK1adabQCx12CS9ctPxlttALHlllxIAWNDks+r4t5tnQ4DSGhh+fRqzVlOhwEkLLfkQqYRAABA3GEGxoZwxOiD7V9Lkk5pfyxbCQAO8CmsosxySdKCmkKF5XM4IiCxuCUXUsDYUB8K6/Kp+//hZCsBwBl+T1BPdHhQktR9zQuqNRQwQCy5JReSgW3wyKOOrdKtNgAAicYtuZACxoY0v09Lxp7rdBgAADjGLbmQRbwAACDuUMAAAIC4QwFjQ10wrOumrdR101aylQAAICG5JReyBsaGiDF6Y9MXVhsAgETjllxIAWNDss+rhy7vbbUBxF7QJOmOT2+z2gBiyy25kE+/Dck+r/7PaQVOhwEktJCS9MLXg5wOA0hYbsmFTCMAAIC4wwyMDeGI0cbKgCSpW14GWwkADvAprIHHvC9JWvrNqWwlAMSYW3IhBYwN9aGwih9fJomtBACn+D1BTet0ryS2EgCc4JZcSAa2wSOPcjNSrDYAAInGLbmQAsaGNL9PK37D4kEAQOJySy5kES8AAIg7FDAAACDuUMDYUBcM65fPrtIvn13FVgIAgITkllxIAWNDxBi9uqZSr66pZCsBAEBCcksuZBGvDck+r+67pKfVBhB7QZOkuz6/2WoDiC235EI+/TYk+7y6prCj02EACS2kJD3z1UVOhwEkLLfkQqYRAABA3GEGxoZIxOiT3fskSR2y0+VlKwEg5rwKq1+LdZKklXt7KsJWAkBMuSUXUsDYUBcK69yHl0hiKwHAKSmeoGZ2+Y0kthIAnOCWXEgGtumYVH5lAIDE5oZc6HwEcSTdn6Q1k4qcDgMAAMe4JReyiBcAAMQdChgAABB3KGBsqA+F9etZH+rXsz5UfYitBAAAicctuZACxoZwxOjF9z/Ti+9/pnCErQQAAInHLbmQRbw2JHm9mjCkm9UGEHsh+fTAzuusNoDYcksupICxwZ/k1U0/6eJ0GEBCC5pk/fWLoU6HASQst+RCphEAAEDcYQbGhkjEaNc39ZKknGNS2EoAcIBXYZ2UtlWStLa2C1sJADHmllxIAWNDXSisAaWLJLGVAOCUFE9Q/zp+jCS2EgCc4JZcSAa2KYlZFwBAgnNDLqSAsSHdn6QtD1zodBgAADjGLbmQRbwAACDuUMAAAIC4w1dINtSHwvrd3A2SpIkXdVdKEosHAQCJxS25kBkYG8IRo2eWf6Jnln/CVgIAgITkllzIDIwNSV6vbj3veKsNIPZC8unRqmFWG0BsuSUX2n7lpUuX6mc/+5ny8/Pl8Xg0Z86cqOeNMbr77rvVtm1bpaWladCgQdq8eXNUn927d2v48OHKyMhQVlaWRo0apT179kT1Wb16tc4++2ylpqaqoKBAkydPtj+6JuZP8ur280/Q7eefIH8SBQzghKBJ1qNVw/Vo1XAFTbLT4QAJxy250PYr7927VyeffLKmTJlyyOcnT56sxx9/XFOnTtWKFSvUokULFRUVqa6uzuozfPhwrVu3TmVlZZo7d66WLl2qG2+80Xo+EAho8ODB6tChg1atWqWHHnpIkyZN0l//+tcjGCIAAGhuPMaYI/4Cy+Px6OWXX9all14qaf/sS35+vn7961/rjjvukCTV1NQoNzdX06dP11VXXaUNGzaoR48eevfdd3XaaadJkubPn68LL7xQn332mfLz8/Xkk0/qt7/9rSorK+X3+yVJ48eP15w5c7Rx48ZGxRYIBJSZmamamhplZGQc6RCjGGMUqAtJkjJSk+TxOH8hHyARdBw/z2p7FFHXlE8lSVvqC2S+5++wjx8sPuqxAYnmaOfCxubvJp372bZtmyorKzVo0CDrsczMTPXv31/l5eWSpPLycmVlZVnFiyQNGjRIXq9XK1assPoMHDjQKl4kqaioSJs2bdLXX399yNeur69XIBCIujW12mBYJ9/7uk6+93XVBsNNfnwAPyzV06CyE0tUdmKJUj0NTocDJBy35MImLWAqKyslSbm5uVGP5+bmWs9VVlYqJycn6vmkpCRlZ2dH9TnUMb79Gt9VWlqqzMxM61ZQUPDjBwQAAFyp2ZyFNGHCBI0ZM8a6HwgEmryISUv2afPvh0hyxz4QAADEmltyYZMWMHl5eZKkqqoqtW3b1nq8qqpKffr0sfrs2rUr6udCoZB2795t/XxeXp6qqqqi+hy4f6DPd6WkpCglJaVJxnE4Ho9HyT4KFwBA4nJLLmzSr5A6deqkvLw8LVq0yHosEAhoxYoVKiwslCQVFhaqurpaq1atsvosXrxYkUhE/fv3t/osXbpUwWDQ6lNWVqYTTzxRxx57bFOGDAAA4pDtAmbPnj2qqKhQRUWFpP0LdysqKrR9+3Z5PB7ddttt+t3vfqd//etfWrNmja655hrl5+dbZyp1795dF1xwgW644QatXLlSb7/9tkaPHq2rrrpK+fn5kqSrr75afr9fo0aN0rp16/T888/rsccei/qKyAkNoYgeeHWDHnh1gxpCEUdjAQDACW7Jhba/Qnrvvfd07rnnWvcPFBUjR47U9OnTdeedd2rv3r268cYbVV1drbPOOkvz589Xamqq9TPPPvusRo8erfPOO09er1dDhw7V448/bj2fmZmp119/XSUlJerbt69at26tu+++O+paMU4IRSL669L/SJJuG3S8/OzEAABIMG7JhT/qOjBudjSuA9MQiujh1zdJku4YfCJX4wVi5NvXgUn2BHVH3jOSpIcrR3zv1Xi5DgzQ9I52Lmxs/m42ZyHFgj/Jq99c2N3pMICEFjTJKt15vdNhAAnLLbmQKQQAABB3mIGxwRij0P9sHZ7k9bCVAOAAjyI6LvkLSdLnwTbfu5UAgKbnllzIJ9+G2mBYx//2NR3/29fYSgBwSKqnQcu6j9Ky7qPYSgBwgFtyIQUMAACIO3yFZENask8f3jPYagMAkGjckgspYGzweDzKTDv8KZsAADR3bsmFfIUEAADiDjMwNjSEIpryxhZJUsm5XbmQHQAg4bglF1LA2BCKRPTYos2SpJt+0pmtBAAACcctuZACxgaf16MRAzpYbQCxF5ZPT39ZbLUBxJZbciF7IQFwnW/vffRjsBcSEH8am7/5DgQAAMQdvkICEGeMsn0BSdLucIYkvs4FEhEzMDbsawip629eVdffvKp9DSGnwwESUpqnXu/3HK73ew5Xmqfe6XCAhOOWXMgMjE0HNrACACBRuSEXUsDYkJrk0/IJ51ltAAASjVtyIQWMDV6vR3mZqU6HAQCAY9ySC1kDAwAA4g4zMDY0hCKa9vY2SdJ1Z3ZiKwEAQMJxSy6kgLEhFImo9LWNkqQRhR3YSgAAkHDckgspYGzweT0aemo7qw0g9sLy6YXd51ltALHlllxIAWNDSpJPf7jiZKfDABJag0nWHZ/d7nQYQMJySy7kOxAAABB3mIEBEGeMdQXeWpMithIAEhMzMDbsawip16QF6jVpAVsJAA5J89RrQ6/LtaHX5WwlADjALbmQGRibvqmjcAEAJDY35EIKGBtSk3x6445zrDYAAInGLbmQAsYGr9ejTq1bOB0GAACOcUsuZA0MAACIO8zA2BAMR/Tcyu2SpGH92ivZR/0HAEgsbsmFFDA2BMMR3f3KOknS5X3bUcAAABKOW3IhBYwNXo9HF/bKs9oAYi8ir+ZVn2m1AcSWW3IhBYwNqck+PTG8r9NhAAmt3vhVsn2C02EACcstuZA/XwAAQNyhgAEAAHGHAsaG2oaw+j+wUP0fWKjahrDT4QAJKc1Tp497X6SPe1+kNE+d0+EACcctuZA1MDYYGVUF6q02AACJxi25kALGhpQkn+b937OsNgAAicYtuZACxgaf16Oe+ZlOhwEAgGPckgtZAwMAAOIOMzA2BMMRzfngc0nSpaccx5V4AQAJxy25kALGhmA4orEvrJYkFfduSwEDAEg4bsmFFDA2eD0enXtiG6sNIPYi8mpx4DSrDSC23JILKWBsSE32adp1/ZwOA0ho9cav6z+e5HQYQMJySy7kzxcAABB3KGAAAEDcoYCxobYhrHMeekPnPPQGWwkADknz1Gn9SUO1/qShbCUAOMAtuZA1MDYYGX381T6rDcAZ6d56p0MAEpZbciEFjA0pST69cHOh1QYAING4JRdSwNjg83p0Wsdsp8MAAMAxbsmFrIEBAABxhxkYG0LhiBasq5IkFfXMVRJX4gUAJBi35MImf9VJkybJ4/FE3bp162Y9X1dXp5KSErVq1UotW7bU0KFDVVVVFXWM7du3q7i4WOnp6crJydHYsWMVCoWaOlTbGsIRlcx4XyUz3ldDOOJ0OAAAxJxbcuFRmYHp2bOnFi5c+L8vkvS/L3P77bdr3rx5mj17tjIzMzV69GhddtllevvttyVJ4XBYxcXFysvL0zvvvKOdO3fqmmuuUXJysh544IGjEW6jeT0e9e+UbbUBxF5EHi3fc5LVBhBbbsmFHmNMk54DNWnSJM2ZM0cVFRUHPVdTU6M2bdpoxowZuvzyyyVJGzduVPfu3VVeXq4BAwbotdde00UXXaQdO3YoNzdXkjR16lSNGzdOX3zxhfx+f6PiCAQCyszMVE1NjTIyMppsfACOvo7j5zXJcT5+sLhJjgMgdhqbv4/KF1ebN29Wfn6+OnfurOHDh2v79u2SpFWrVikYDGrQoEFW327duql9+/YqLy+XJJWXl6tXr15W8SJJRUVFCgQCWrdu3WFfs76+XoFAIOoGAACapyYvYPr376/p06dr/vz5evLJJ7Vt2zadffbZ+uabb1RZWSm/36+srKyon8nNzVVlZaUkqbKyMqp4OfD8gecOp7S0VJmZmdatoKCgaQcGAABco8nXwAwZMsRq9+7dW/3791eHDh00a9YspaWlNfXLWSZMmKAxY8ZY9wOBQJMXMXXBsH7+xDuSpJd/eYZSk7mYHRBraZ46Let+vSTprA1PqdakOhwRkFjckguP+mnUWVlZOuGEE7Rlyxadf/75amhoUHV1ddQsTFVVlfLy8iRJeXl5WrlyZdQxDpyldKDPoaSkpCglJaXpB/AtEWO0YWfAagNwRqskviIGnOKWXHjUT97es2ePtm7dqrZt26pv375KTk7WokWLrOc3bdqk7du3q7Bw/2WJCwsLtWbNGu3atcvqU1ZWpoyMDPXo0eNoh/u9UpJ8emZUPz0zqh9bCQAAEpJbcmGTz8Dccccd+tnPfqYOHTpox44duueee+Tz+TRs2DBlZmZq1KhRGjNmjLKzs5WRkaFf/epXKiws1IABAyRJgwcPVo8ePTRixAhNnjxZlZWVmjhxokpKSo76DMsP8Xk9Ovv4No7GAACAk9ySC5u8gPnss880bNgwffXVV2rTpo3OOussLV++XG3a7B/sI488Iq/Xq6FDh6q+vl5FRUV64oknrJ/3+XyaO3eubrnlFhUWFqpFixYaOXKk7rvvvqYOFQAAxKkmvw6MWxyN68CEwhEt3fyFJGng8W3YSgA4Sr7vOjBpnjpt6LX/OlLd17zwvYt4G3MdmO++FteOAb7f0c6Fjc3f7IVkQ0M4ouunvydJWn9fEQUMACDhuCUXUsDY4PV41LtdptUGEHsRefThvuOtNoDYcksupICxITXZp3+NPsvpMICEVm9SdMmWR5wOA0hYbsmFfAcCAADiDgUMAACIOxQwNtQFwxr65Dsa+uQ7qguGnQ4HSEipnjot63a9lnW7XqmeOqfDARKOW3Iha2BsiBijVZ98bbUBxJ5HUjv/LqsNILbckgspYGzw+7z6y4i+VhsAgETjllxIAWNDks+rop6H31ASAIDmzi25kGkEAAAQd5iBsSEcMVq5bbckqV+nbPm8fAMPxJPv26IAQOO4JRdSwNhQHwpr2N+WS9p/+eR0P78+AEBicUsuJAPb4JFHx+e0tNoAYs9I+qiuvdUGEFtuyYUUMDak+X0qG/MTp8MAElqdSdXgj55wOgwgYbklF7KIFwAAxB0KGAAAEHcoYGyoC4b1X39fof/6+wq2EgAckuqp0+sn/FKvn/BLthIAHOCWXMgaGBsixmjZli+tNoDY80g6IXW71QYQW27JhRQwNvh9Xj16ZR+rDQBAonFLLqSAsSHJ59WlpxzndBgAADjGLbmQaQQAABB3mIGxIRwxWvt5jSTppOMy2UoAAJBw3JILmYGxoT4U1iVT3tYlU95WfYizkAAAicctuZAZGBs88ui4rDSrDSD2jKTPGnKsNoDYcksu9BjTPM8HDgQCyszMVE1NjTIyMpwOB4ANTu4a/fGDxY69NoDG52++QgIAAHGHr5AAxNR3Z1eY8QBwJChgbKgLhvWr5z6QJP1p2ClKTfY5HBHgbkfjq6AUT71mdRkvSbpi64OqNylN/hoADs8tuZACxoaIMSpbX2W1AcSeV0Ynp2+22gBiyy25kALGhmSfV6WX9bLaAAAkGrfkQgoYG5J9Xg3r197pMAAAcIxbciEFDABHOXnKNID4RQFjQyRitOWLPZKkrm1aystWAgCABOOWXEgBY0NdKKzBjyyVJK2/r0jpfn59AIDE4pZcSAa2KbuF3+kQgIT3VYirawNOckMupICxId2fpPfvOt/pMICEVmtS1Xf9DKfDABKWW3Ih5wIDAIC4QwEDAADiDgWMDXXBsG6d+YFunfmB6oJhp8MBElKKp14zO4/XzM7jleKpdzocIOG4JRdSwNgQMUavVOzQKxU72EoAcIhXRgNartWAlmvZSgBwgFtyIYt4bUj2eXXXRT2sNgAAicYtuZACxoZkn1ejzurkdBgAADjGLbmQaQQAABB3mIGxIRIx+ry6VpJ0XFYaWwkAABKOW3IhMzA21IXCOnvyGzp78huqC3EWEgAg8bglFzIDY1Nass/pEICEty+S4nQIQEJzQy6kgLEh3Z+kDfdf4HQYQEKrNanqsfZFp8MAEpZbciFfIQEAgLhDAQMAAOIOBYwN9aGwxr+4WuNfXK16FvECjkjxNOipjpP0VMdJSvE0OB0OkHDckgspYGwIR4xmvvupZr77qcIRLmEOOMGriH6a8Z5+mvGevIo4HQ6QcNySC1nEa0OS16s7Bp9gtQEASDRuyYUUMDb4k7wa/dPjnQ4DAADHuCUXunoaYcqUKerYsaNSU1PVv39/rVy50umQAACAC7i2gHn++ec1ZswY3XPPPXr//fd18sknq6ioSLt27XIsJmOMvtpTr6/21Ms4uIU4AABOcUsudG0B88c//lE33HCDrrvuOvXo0UNTp05Venq6nnrqKcdiqg2G1fd3C9X3dwtVG+QsJABA4nFLLnTlGpiGhgatWrVKEyZMsB7zer0aNGiQysvLD/kz9fX1qq+vt+7X1NRIkgKBQJPFta8hpEj9Puu4Ib8rf32Aaxz4vDSlsKdOgf85bLh+nyKmac9Easp/M4Dm6GjnwgOfwR+a3XFlBv7yyy8VDoeVm5sb9Xhubq42btx4yJ8pLS3Vvffee9DjBQUFRyXGto8elcMCaIRMq3VN0x/70SY/JNBsHc1c+M033ygzM/Owz7uygDkSEyZM0JgxY6z7kUhEu3fvVqtWreTxOLPV96EEAgEVFBTo008/VUZGhtPhHBWJMEYpMcbJGJuHRBijlBjjTIQxGmP0zTffKD8//3v7ubKAad26tXw+n6qqqqIer6qqUl5e3iF/JiUlRSkp0TvUZmVlHa0Qf7SMjIxm+z/fAYkwRikxxskYm4dEGKOUGONs7mP8vpmXA1y5iNfv96tv375atGiR9VgkEtGiRYtUWFjoYGQAAMANXDkDI0ljxozRyJEjddppp6lfv3569NFHtXfvXl133XVOhwYAABzm2gLmyiuv1BdffKG7775blZWV6tOnj+bPn3/Qwt54k5KSonvuueegr7uak0QYo5QY42SMzUMijFFKjHEmwhgby2O4IhsAAIgzrlwDAwAA8H0oYAAAQNyhgAEAAHGHAgYAAMQdCpjv6Nixozwez0G3kpISSdI555xz0HM333xz1DG2b9+u4uJipaenKycnR2PHjlUoFIrqs2TJEp166qlKSUlR165dNX369INimTJlijp27KjU1FT1799fK1eujHq+rq5OJSUlatWqlVq2bKmhQ4cedPG/IxmjJJWXl+unP/2pWrRooYyMDA0cOFC1tbXW87t379bw4cOVkZGhrKwsjRo1Snv27Il6ndWrV+vss89WamqqCgoKNHny5INimT17trp166bU1FT16tVLr776atTzxhjdfffdatu2rdLS0jRo0CBt3rz5R43x448/PuRzHo9Hs2fPto7h9vfxh8YpSZWVlRoxYoTy8vLUokULnXrqqXrxxRejjhHP76Ukbd26VT//+c/Vpk0bZWRk6Iorrjjo9+f2MYbDYd11113q1KmT0tLS1KVLF91///1Re8E05thuHmdjxvjSSy9p8ODB1hXUKyoqDjpOYz4vsfrsHsk4g8Ggxo0bp169eqlFixbKz8/XNddcox07dkQdx83vpWsYRNm1a5fZuXOndSsrKzOSzBtvvGGMMeYnP/mJueGGG6L61NTUWD8fCoXMSSedZAYNGmQ++OAD8+qrr5rWrVubCRMmWH3+85//mPT0dDNmzBizfv1686c//cn4fD4zf/58q8/MmTON3+83Tz31lFm3bp254YYbTFZWlqmqqrL63HzzzaagoMAsWrTIvPfee2bAgAHmjDPO+NFjfOedd0xGRoYpLS01a9euNRs3bjTPP/+8qaurs45xwQUXmJNPPtksX77cvPXWW6Zr165m2LBh1vM1NTUmNzfXDB8+3Kxdu9Y899xzJi0tzfzlL3+x+rz99tvG5/OZyZMnm/Xr15uJEyea5ORks2bNGqvPgw8+aDIzM82cOXPMhx9+aC6++GLTqVMnU1tbe8RjDIVCUc/t3LnT3HvvvaZly5bmm2++iZv3sTHv5fnnn29OP/10s2LFCrN161Zz//33G6/Xa95///1m8V7u2bPHdO7c2fz85z83q1evNqtXrzaXXHKJOf300004HI6bMf7+9783rVq1MnPnzjXbtm0zs2fPNi1btjSPPfaYrWO7eZyNGePTTz9t7r33XvO3v/3NSDIffPDBQcf5oc9LLD+7RzLO6upqM2jQIPP888+bjRs3mvLyctOvXz/Tt2/fqOO4+b10CwqYH3DrrbeaLl26mEgkYozZX8Dceuuth+3/6quvGq/XayorK63HnnzySZORkWHq6+uNMcbceeedpmfPnlE/d+WVV5qioiLrfr9+/UxJSYl1PxwOm/z8fFNaWmqM2f8hSE5ONrNnz7b6bNiwwUgy5eXlP2qM/fv3NxMnTjxs//Xr1xtJ5t1337Uee+2114zH4zGff/65McaYJ554whx77LHWmI0xZty4cebEE0+07l9xxRWmuLg46tj9+/c3N910kzHGmEgkYvLy8sxDDz1kPV9dXW1SUlLMc88996PG+F19+vQx119/vXU/Ht/HQ42zRYsW5umnn47qk52dbf72t78ZY+L/vVywYIHxer1Rf0RUV1cbj8djysrK4maMxcXFUf//GWPMZZddZoYPH97oY7t9nD80xm/btm3bIQuYxnxeYvXZbYpxHrBy5UojyXzyySfGGPe/l27BV0jfo6GhQf/93/+t66+/PmpDyGeffVatW7fWSSedpAkTJmjfvn3Wc+Xl5erVq1fUBfeKiooUCAS0bt06q8+gQYOiXquoqEjl5eXW665atSqqj9fr1aBBg6w+q1atUjAYjOrTrVs3tW/f3upzJGPctWuXVqxYoZycHJ1xxhnKzc3VT37yEy1btixqjFlZWTrttNOsxwYNGiSv16sVK1ZYfQYOHCi/3x81xk2bNunrr79u1O9h27ZtqqysjOqTmZmp/v37/6gxfteqVatUUVGhUaNGRY0xnt7Hw43zjDPO0PPPP6/du3crEolo5syZqqur0znnnGONIZ7fy/r6enk8nqiLeqWmpsrr9Vr/z8bDGM844wwtWrRIH330kSTpww8/1LJlyzRkyJBGH9vt4/yhMTZGYz4vsfrsNuU4a2pq5PF4rP373P5euoVrr8TrBnPmzFF1dbWuvfZa67Grr75aHTp0UH5+vlavXq1x48Zp06ZNeumllyTtX3Pw3asFH7hfWVn5vX0CgYBqa2v19ddfKxwOH7LPxo0brWP4/f6DNqzMzc21XudIxvif//xHkjRp0iQ9/PDD6tOnj55++mmdd955Wrt2rY4//nhVVlYqJycn6jhJSUnKzs6OGmOnTp0O+3s49thjD/t7+PYxvv1zTTXG7/rHP/6h7t2764wzzrAei7f38XDjnDVrlq688kq1atVKSUlJSk9P18svv6yuXbtarx/P7+WAAQPUokULjRs3Tg888ICMMRo/frzC4bB27twZN2McP368AoGAunXrJp/Pp3A4rN///vcaPnx4o4/t9nH+0BgbozGfl1h9dptqnHV1dRo3bpyGDRtmbc7o9vfSLShgvsc//vEPDRkyJGpL7xtvvNFq9+rVS23bttV5552nrVu3qkuXLk6E+aN8d4yRSESSdNNNN1n7Tp1yyilatGiRnnrqKZWWljoW65E61Pt4QG1trWbMmKG77rrLgcia1qHGedddd6m6uloLFy5U69atNWfOHF1xxRV666231KtXLwejPTLfHWObNm00e/Zs3XLLLXr88cfl9Xo1bNgwnXrqqfJ642eCedasWXr22Wc1Y8YM9ezZUxUVFbrtttuUn5+vkSNHOh1ek0iEMUr2xhkMBnXFFVfIGKMnn3zSoYjjFwXMYXzyySdauHChNbNyOP3795ckbdmyRV26dFFeXt5BK9UPrJDPy8uz/vvdVfNVVVXKyMhQWlqafD6ffD7fIft8+xgNDQ2qrq6O+mvk232OZIxt27aVJPXo0SOqb/fu3bV9+3brtXft2hX1fCgU0u7du39wjI35PXz7+QOPHYjrwP0+ffoc8Ri/7YUXXtC+fft0zTXXRD0eT+/j4ca5detW/fnPf9batWvVs2dPSdLJJ5+st956S1OmTNHUqVObxXs5ePBgbd26VV9++aWSkpKUlZWlvLw8de7c2Xptt49x7NixGj9+vK666ipJ+/84+uSTT1RaWqqRI0c26thuH+cPjbExGvN5idVn98eO80Dx8sknn2jx4sXW7MuB+Nz8XrpF/PyJEmPTpk1TTk6OiouLv7ffgdP8Drz5hYWFWrNmTdT/fGVlZcrIyLCKgsLCQi1atCjqOGVlZSosLJQk+f1+9e3bN6pPJBLRokWLrD59+/ZVcnJyVJ9NmzZp+/btVp8jGWPHjh2Vn5+vTZs2RfX96KOP1KFDByv+6upqrVq1ynp+8eLFikQiVkFXWFiopUuXKhgMRo3xxBNP1LHHHtuo30OnTp2Ul5cX1ScQCGjFihU/aozf9o9//EMXX3yx2rRpE/V4PL2PhxvngbVZ352J8Pl81kxbc3ovW7duraysLC1evFi7du3SxRdfHDdj3Ldv3/e+T405ttvH+UNjbIzGfF5i9dn9MeM8ULxs3rxZCxcuVKtWraL6u/29dA2nVxG7UTgcNu3btzfjxo2LenzLli3mvvvuM++9957Ztm2beeWVV0znzp3NwIEDrT4HTuEbPHiwqaioMPPnzzdt2rQ55Cl8Y8eONRs2bDBTpkw55Cl8KSkpZvr06Wb9+vXmxhtvNFlZWVEr62+++WbTvn17s3jxYvPee++ZwsJCU1hY+KPGaIwxjzzyiMnIyDCzZ882mzdvNhMnTjSpqalmy5YtVp8LLrjAnHLKKWbFihVm2bJl5vjjj486xa+6utrk5uaaESNGmLVr15qZM2ea9PT0g07xS0pKMg8//LDZsGGDueeeew55il9WVpZ55ZVXrFNkG3uK3/eN0RhjNm/ebDwej3nttdcOei5e3sfvG2dDQ4Pp2rWrOfvss82KFSvMli1bzMMPP2w8Ho+ZN2+e1S/e38unnnrKlJeXmy1btphnnnnGZGdnmzFjxkT1cfsYR44caY477jjr1NuXXnrJtG7d2tx55522ju3mcTZmjF999ZX54IMPzLx584wkM3PmTPPBBx+YnTt3Wn1+6PMSy8/ukYyzoaHBXHzxxaZdu3amoqIi6hIB3z6jyM3vpVtQwBzCggULjCSzadOmqMe3b99uBg4caLKzs01KSorp2rWrGTt2bNQpnMYY8/HHH5shQ4aYtLQ007p1a/PrX//aBIPBqD5vvPGG6dOnj/H7/aZz585m2rRpB8Xxpz/9ybRv3974/X7Tr18/s3z58qjna2trzS9/+Utz7LHHmvT0dPPzn/886oN+JGM8oLS01LRr186kp6ebwsJC89Zbb0U9/9VXX5lhw4aZli1bmoyMDHPddddZ11A54MMPPzRnnXWWSUlJMccdd5x58MEHD3qdWbNmmRNOOMH4/X7Ts2fPqMRqzP7T/O666y6Tm5trUlJSzHnnnXfYmO2OccKECaagoCDqeiHfFg/v4w+N86OPPjKXXXaZycnJMenp6aZ3794HnVYd7+/luHHjTG5urklOTjbHH3+8+cMf/nDQ6fJuH2MgEDC33nqrad++vUlNTTWdO3c2v/3tb6MSWmOO7eZxNmaM06ZNM5IOut1zzz1Wn8Z8XmL12T2ScR44RfxQtwPXbzLG3e+lW3iM+dZlEAEAAOIAa2AAAEDcoYABAABxhwIGAADEHQoYAAAQdyhgAABA3KGAAQAAcYcCBgAAxB0KGAAAEHcoYAAAQNyhgAEAAHGHAgYAAMQdChgAABB3/j+jrCpi9LDHCQAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "checking contiguity of final HDs\n",
      "working on HD 0 out of 8941\n",
      "working on HD 800 out of 8941\n",
      "working on HD 1600 out of 8941\n",
      "working on HD 2400 out of 8941\n",
      "working on HD 3200 out of 8941\n",
      "working on HD 4000 out of 8941\n",
      "working on HD 4800 out of 8941\n",
      "working on HD 5600 out of 8941\n",
      "working on HD 6400 out of 8941\n",
      "working on HD 7200 out of 8941\n",
      "working on HD 8000 out of 8941\n",
      "working on HD 8800 out of 8941\n",
      "all done checking HD and complement contiguity for all 8941 HDs\n"
     ]
    }
   ],
   "source": [
    "patchedUse, unpUse = [0.]*nUnits, [0.]*nUnits\n",
    "for t in popHDlist:\n",
    "    if homeU[t] not in HDunitList[t]:\n",
    "        print(\"WARNING - we lost home unit\",homeU[t],\"from HD\",t)\n",
    "    for u in HDunitList[t]:\n",
    "        patchedUse[u] += HDweight[t] * nDistricts\n",
    "    if t in hasSplitUnit: #hasSplitUnit[t] == 1:\n",
    "        unitUse[splitUnitNo[t]] -= (1. - splitUnitFrac[t]) * nDistricts * HDweight[t]\n",
    "#    for u in unpatchedHDlist[t]:\n",
    "#        unpUse[u] += HDweight[t] * nDistricts\n",
    "plt.hist(patchedUse,bins=50, label=\"patched\",histtype=\"step\")\n",
    "#plt.hist(unpUse, bins=50, label=\"unpatched\",histtype=\"step\")\n",
    "plt.legend()\n",
    "plt.show()\n",
    "patchedAvg, patchedSD = getWeightedAvgAndSD(patchedUse,unitPop)\n",
    "#unpatchedAvg, unpatchedSD = getWeightedAvgAndSD(unpUse,unitPop)\n",
    "print(\" patched use avg\", r5(patchedAvg),\"and SD\",r5(patchedSD) )\n",
    "#print(\"unpatched, patched use avgs are\",r5(unpatchedAvg), r5(patchedAvg),\"and their SDs are\",r5(unpatchedSD), r5(patchedSD) )\n",
    "print(\"And here is the pop distro\")\n",
    "plt.hist([HDvPop[t] for t in popHDlist])\n",
    "plt.axvline(aDP, ls=\"--\",color=\"orange\")\n",
    "plt.axvline(0.995*aDP, ls=\"dotted\")\n",
    "plt.axvline(1.005*aDP, ls=\"dotted\")\n",
    "plt.show()\n",
    "print(\"checking contiguity of final HDs\")\n",
    "for t in popHDlist:\n",
    "    if t%800 == 0:\n",
    "        print(\"working on HD\",t,\"out of\",nHDs)\n",
    "    unbroken, noEnclave, sList, eList = enclaveCheck(HDunitList[t], unitNbrs)  #these HDunitLists now appear to be sets\n",
    "    if not unbroken or not noEnclave:\n",
    "        print(\"uh-oh, HD\",t,\"has contiguity, complement-contiguity of\",unbroken, noEnclave)\n",
    "print(\"all done checking HD and complement contiguity for all\",nHDs,\"HDs\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 167,
   "id": "4140cd4d-7aaa-4fb2-aa01-25f195f30183",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "save these semi-patched results to temp file\n"
     ]
    }
   ],
   "source": [
    "print(\"save these semi-patched results to temp file\")\n",
    "tList = [t for t in range(nHDs)]\n",
    "outDF = pd.DataFrame( {\"vtd\":tList,\"HDweight\":HDweight,\"HDvPop\":HDvPop,\"HDunitList\":HDunitList,\n",
    "                      \"splitUnitNo\":splitUnitNo,\"splitUnitFrac\":splitUnitFrac,\n",
    "                       \"centroid x\":HDCPx, \"centroid y\":HDCPy, \"homeU\":homeU, \"homeC\":homeC } )\n",
    "outname = STATE+str(int(nHDs))+\"_\"+str(nDistricts)+\"COI615_patchto087.csv\" #\"contigUnpatchedB.csv\" unpatchedContigGoodPop.csv\n",
    "outpath = \"2024state_HD_output/\"+outname\n",
    "outDF.to_csv(outpath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 168,
   "id": "1d7d3c5f-4f94-4b50-98f4-632f5d741bf5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "unitUse by unitPop\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "underPatchedUnitList = [HDunitList[t].copy() for t in range(nHDs)] #safekeeping\n",
    "plt.scatter(unitPop,patchedUse,label=\"patched\")\n",
    "#plt.scatter(unitPop,unpatchedUnitUse,label=\"unpatched\")\n",
    "print(\"unitUse by unitPop\")\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e40ea005-073b-47dd-aa25-c5e77461e57e",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "id": "6e54e08e-d07a-418f-b730-7bbc9d336a23",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.05 = default maxSD. Reco'ing 0.05 for blocky\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter maxSD 0.05\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "default use threshold for moving on to next overused unit is 1.02\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter updated stopMaxUse value 1.02\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "there are currently 319 units out of 4210 with usage above 1.02\n",
      "maxExchangePop is currently 0.25 fraction of avgDistrictPop\n",
      "this block reduces overuse, with exchanges up to 29796\n",
      "current avg and SD of unit usage are 1.00727 0.07009 . Now trying to reduce up to 319 units' overusage\n",
      "starting to reduce usage for unit 4056 with usage 1.41591 . Total units tried = 1\n",
      "try to drop unit 4056 from 0 th HD out of 115 possible.  usage down to 1.4159088628550032\n",
      "try to drop unit 4056 from 30 th HD out of 115 possible.  usage down to 1.229427766451228\n",
      "try to drop unit 4056 from 60 th HD out of 115 possible.  usage down to 1.197645601726247\n",
      "try to drop unit 4056 from 90 th HD out of 115 possible.  usage down to 1.197645601726247\n",
      "all done trying to reduce usage of unit 4056 final usage = 1.19765 0 sec elapsed 19 58 successful, failed patches, couldn't start= 15\n",
      "current avg and SD of usage are 1.00726 0.06849\n",
      "starting to reduce usage for unit 2762 with usage 1.27038 . Total units tried = 2\n",
      "try to drop unit 2762 from 0 th HD out of 104 possible.  usage down to 1.2703804449154796\n",
      "try to drop unit 2762 from 30 th HD out of 104 possible.  usage down to 1.2703804449154796\n",
      "try to drop unit 2762 from 60 th HD out of 104 possible.  usage down to 1.2308457141382516\n",
      "all done trying to reduce usage of unit 2762 final usage = 1.21216 1 sec elapsed 5 68 successful, failed patches, couldn't start= 11\n",
      "current avg and SD of usage are 1.00724 0.06826\n",
      "starting to reduce usage for unit 2810 with usage 1.23504 . Total units tried = 3\n",
      "try to drop unit 2810 from 0 th HD out of 78 possible.  usage down to 1.2350408256383851\n",
      "all done trying to reduce usage of unit 2810 final usage = 1.01179 3 sec elapsed 20 2 successful, failed patches, couldn't start= 2\n",
      "current avg and SD of usage are 1.00709 0.06673\n",
      "starting to reduce usage for unit 2861 with usage 1.21405 . Total units tried = 4\n",
      "try to drop unit 2861 from 0 th HD out of 83 possible.  usage down to 1.214048487691651\n",
      "all done trying to reduce usage of unit 2861 final usage = 1.01476 3 sec elapsed 14 4 successful, failed patches, couldn't start= 8\n",
      "current avg and SD of usage are 1.00698 0.06592\n",
      "starting to reduce usage for unit 787 with usage 1.21349 . Total units tried = 5\n",
      "try to drop unit 787 from 0 th HD out of 110 possible.  usage down to 1.2134947329738244\n",
      "try to drop unit 787 from 30 th HD out of 110 possible.  usage down to 1.058762240402996\n",
      "all done trying to reduce usage of unit 787 final usage = 1.00949 5 sec elapsed 21 0 successful, failed patches, couldn't start= 39\n",
      "current avg and SD of usage are 1.00682 0.06513\n",
      "starting to reduce usage for unit 2483 with usage 1.19846 . Total units tried = 6\n",
      "try to drop unit 2483 from 0 th HD out of 71 possible.  usage down to 1.198459453357211\n",
      "try to drop unit 2483 from 30 th HD out of 71 possible.  usage down to 1.0855186615506869\n",
      "all done trying to reduce usage of unit 2483 final usage = 1.07864 6 sec elapsed 12 22 successful, failed patches, couldn't start= 23\n",
      "current avg and SD of usage are 1.00684 0.06442\n",
      "starting to reduce usage for unit 619 with usage 1.1981 . Total units tried = 7\n",
      "try to drop unit 619 from 0 th HD out of 80 possible.  usage down to 1.1980986737681494\n",
      "try to drop unit 619 from 30 th HD out of 80 possible.  usage down to 1.0267703201028182\n",
      "all done trying to reduce usage of unit 619 final usage = 1.00501 6 sec elapsed 13 14 successful, failed patches, couldn't start= 6\n",
      "current avg and SD of usage are 1.00682 0.06386\n",
      "starting to reduce usage for unit 3971 with usage 1.19663 . Total units tried = 8\n",
      "try to drop unit 3971 from 0 th HD out of 86 possible.  usage down to 1.1966303847431565\n",
      "all done trying to reduce usage of unit 3971 final usage = 1.01288 7 sec elapsed 15 4 successful, failed patches, couldn't start= 7\n",
      "current avg and SD of usage are 1.00669 0.0632\n",
      "starting to reduce usage for unit 2816 with usage 1.18244 . Total units tried = 9\n",
      "try to drop unit 2816 from 0 th HD out of 97 possible.  usage down to 1.1824425176496502\n",
      "try to drop unit 2816 from 30 th HD out of 97 possible.  usage down to 1.140038330606328\n",
      "try to drop unit 2816 from 60 th HD out of 97 possible.  usage down to 1.127486556997942\n",
      "all done trying to reduce usage of unit 2816 final usage = 1.12749 7 sec elapsed 5 47 successful, failed patches, couldn't start= 26\n",
      "current avg and SD of usage are 1.00666 0.06301\n",
      "starting to reduce usage for unit 2828 with usage 1.17732 . Total units tried = 10\n",
      "try to drop unit 2828 from 0 th HD out of 68 possible.  usage down to 1.177316091396526\n",
      "try to drop unit 2828 from 30 th HD out of 68 possible.  usage down to 1.0251761777328101\n",
      "all done trying to reduce usage of unit 2828 final usage = 1.01651 8 sec elapsed 10 24 successful, failed patches, couldn't start= 1\n",
      "current avg and SD of usage are 1.00662 0.06229\n",
      "starting to reduce usage for unit 4044 with usage 1.17255 . Total units tried = 11\n",
      "try to drop unit 4044 from 0 th HD out of 107 possible.  usage down to 1.1725504447325312\n",
      "all done trying to reduce usage of unit 4044 final usage = 1.01902 10 sec elapsed 17 4 successful, failed patches, couldn't start= 1\n",
      "current avg and SD of usage are 1.00659 0.06193\n",
      "starting to reduce usage for unit 4130 with usage 1.16899 . Total units tried = 12\n",
      "try to drop unit 4130 from 0 th HD out of 89 possible.  usage down to 1.1689929901801963\n",
      "all done trying to reduce usage of unit 4130 final usage = 1.01984 11 sec elapsed 12 1 successful, failed patches, couldn't start= 3\n",
      "current avg and SD of usage are 1.00651 0.06163\n",
      "starting to reduce usage for unit 4169 with usage 1.16818 . Total units tried = 13\n",
      "try to drop unit 4169 from 0 th HD out of 105 possible.  usage down to 1.1681791385493092\n",
      "try to drop unit 4169 from 30 th HD out of 105 possible.  usage down to 1.1510630836287816\n",
      "try to drop unit 4169 from 60 th HD out of 105 possible.  usage down to 1.1415234000774808\n",
      "all done trying to reduce usage of unit 4169 final usage = 1.12669 12 sec elapsed 4 36 successful, failed patches, couldn't start= 44\n",
      "current avg and SD of usage are 1.0065 0.06153\n",
      "starting to reduce usage for unit 2768 with usage 1.16799 . Total units tried = 14\n",
      "try to drop unit 2768 from 0 th HD out of 38 possible.  usage down to 1.1679945536432497\n",
      "all done trying to reduce usage of unit 2768 final usage = 1.01115 19 sec elapsed 13 16 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00639 0.05972\n",
      "starting to reduce usage for unit 779 with usage 1.16622 . Total units tried = 15\n",
      "try to drop unit 779 from 0 th HD out of 50 possible.  usage down to 1.1662158263671722\n",
      "try to drop unit 779 from 30 th HD out of 50 possible.  usage down to 1.1662158263671722\n",
      "all done trying to reduce usage of unit 779 final usage = 1.16622 19 sec elapsed 0 0 successful, failed patches, couldn't start= 40\n",
      "current avg and SD of usage are 1.00639 0.05972\n",
      "starting to reduce usage for unit 4149 with usage 1.16622 . Total units tried = 16\n",
      "try to drop unit 4149 from 0 th HD out of 86 possible.  usage down to 1.1662158263671722\n",
      "try to drop unit 4149 from 30 th HD out of 86 possible.  usage down to 1.1662158263671722\n",
      "try to drop unit 4149 from 60 th HD out of 86 possible.  usage down to 1.1662158263671722\n",
      "all done trying to reduce usage of unit 4149 final usage = 1.16622 19 sec elapsed 0 0 successful, failed patches, couldn't start= 69\n",
      "current avg and SD of usage are 1.00639 0.05972\n",
      "starting to reduce usage for unit 4150 with usage 1.16622 . Total units tried = 17\n",
      "try to drop unit 4150 from 0 th HD out of 89 possible.  usage down to 1.1662158263671722\n",
      "try to drop unit 4150 from 30 th HD out of 89 possible.  usage down to 1.1662158263671722\n",
      "try to drop unit 4150 from 60 th HD out of 89 possible.  usage down to 1.1662158263671722\n",
      "all done trying to reduce usage of unit 4150 final usage = 1.16622 20 sec elapsed 0 0 successful, failed patches, couldn't start= 72\n",
      "current avg and SD of usage are 1.00639 0.05972\n",
      "starting to reduce usage for unit 2802 with usage 1.16198 . Total units tried = 18\n",
      "try to drop unit 2802 from 0 th HD out of 64 possible.  usage down to 1.1619787637518872\n",
      "all done trying to reduce usage of unit 2802 final usage = 1.01378 20 sec elapsed 12 3 successful, failed patches, couldn't start= 4\n",
      "current avg and SD of usage are 1.00631 0.05907\n",
      "starting to reduce usage for unit 782 with usage 1.15529 . Total units tried = 19\n",
      "try to drop unit 782 from 0 th HD out of 59 possible.  usage down to 1.1552917560208777\n",
      "try to drop unit 782 from 30 th HD out of 59 possible.  usage down to 1.1552917560208777\n",
      "all done trying to reduce usage of unit 782 final usage = 1.15529 20 sec elapsed 0 8 successful, failed patches, couldn't start= 40\n",
      "current avg and SD of usage are 1.00631 0.05907\n",
      "starting to reduce usage for unit 2766 with usage 1.15037 . Total units tried = 20\n",
      "try to drop unit 2766 from 0 th HD out of 48 possible.  usage down to 1.1503746939147592\n",
      "try to drop unit 2766 from 30 th HD out of 48 possible.  usage down to 1.1008723782132215\n",
      "all done trying to reduce usage of unit 2766 final usage = 1.06311 21 sec elapsed 6 20 successful, failed patches, couldn't start= 13\n",
      "current avg and SD of usage are 1.0063 0.05803\n",
      "starting to reduce usage for unit 2509 with usage 1.14686 . Total units tried = 21\n",
      "try to drop unit 2509 from 0 th HD out of 74 possible.  usage down to 1.1468595819056493\n",
      "try to drop unit 2509 from 30 th HD out of 74 possible.  usage down to 1.1468595819056493\n",
      "all done trying to reduce usage of unit 2509 final usage = 1.11293 21 sec elapsed 2 28 successful, failed patches, couldn't start= 30\n",
      "current avg and SD of usage are 1.00629 0.05787\n",
      "starting to reduce usage for unit 777 with usage 1.1449 . Total units tried = 22\n",
      "try to drop unit 777 from 0 th HD out of 45 possible.  usage down to 1.1449046599465553\n",
      "try to drop unit 777 from 30 th HD out of 45 possible.  usage down to 1.1006210629511723\n",
      "all done trying to reduce usage of unit 777 final usage = 1.10062 21 sec elapsed 4 30 successful, failed patches, couldn't start= 2\n",
      "current avg and SD of usage are 1.0063 0.05725\n",
      "starting to reduce usage for unit 1033 with usage 1.13909 . Total units tried = 23\n",
      "try to drop unit 1033 from 0 th HD out of 82 possible.  usage down to 1.1390902354073158\n",
      "all done trying to reduce usage of unit 1033 final usage = 1.01812 22 sec elapsed 11 0 successful, failed patches, couldn't start= 2\n",
      "current avg and SD of usage are 1.00624 0.0569\n",
      "starting to reduce usage for unit 4154 with usage 1.13432 . Total units tried = 24\n",
      "try to drop unit 4154 from 0 th HD out of 95 possible.  usage down to 1.1343245887431856\n",
      "try to drop unit 4154 from 30 th HD out of 95 possible.  usage down to 1.0922811812888873\n",
      "try to drop unit 4154 from 60 th HD out of 95 possible.  usage down to 1.0489037283775402\n",
      "all done trying to reduce usage of unit 4154 final usage = 1.03648 23 sec elapsed 9 57 successful, failed patches, couldn't start= 10\n",
      "current avg and SD of usage are 1.00619 0.05673\n",
      "starting to reduce usage for unit 1043 with usage 1.12879 . Total units tried = 25\n",
      "try to drop unit 1043 from 0 th HD out of 94 possible.  usage down to 1.1287870415630574\n",
      "try to drop unit 1043 from 30 th HD out of 94 possible.  usage down to 1.1044134437472999\n",
      "try to drop unit 1043 from 60 th HD out of 94 possible.  usage down to 1.1044134437472999\n",
      "all done trying to reduce usage of unit 1043 final usage = 1.09186 23 sec elapsed 4 39 successful, failed patches, couldn't start= 33\n",
      "current avg and SD of usage are 1.00618 0.05657\n",
      "starting to reduce usage for unit 2503 with usage 1.12828 . Total units tried = 26\n",
      "try to drop unit 2503 from 0 th HD out of 68 possible.  usage down to 1.1282752379602323\n",
      "try to drop unit 2503 from 30 th HD out of 68 possible.  usage down to 1.0451616889196467\n",
      "all done trying to reduce usage of unit 2503 final usage = 1.03061 24 sec elapsed 9 13 successful, failed patches, couldn't start= 33\n",
      "current avg and SD of usage are 1.00613 0.05577\n",
      "starting to reduce usage for unit 4103 with usage 1.12802 . Total units tried = 27\n",
      "try to drop unit 4103 from 0 th HD out of 98 possible.  usage down to 1.1280235312702045\n",
      "all done trying to reduce usage of unit 4103 final usage = 1.01168 25 sec elapsed 12 2 successful, failed patches, couldn't start= 1\n",
      "current avg and SD of usage are 1.00605 0.05545\n",
      "starting to reduce usage for unit 1045 with usage 1.12744 . Total units tried = 28\n",
      "try to drop unit 1045 from 0 th HD out of 75 possible.  usage down to 1.127436215659978\n",
      "try to drop unit 1045 from 30 th HD out of 75 possible.  usage down to 1.0887824582977819\n",
      "all done trying to reduce usage of unit 1045 final usage = 1.08878 25 sec elapsed 3 12 successful, failed patches, couldn't start= 45\n",
      "current avg and SD of usage are 1.00604 0.05526\n",
      "starting to reduce usage for unit 4050 with usage 1.12713 . Total units tried = 29\n",
      "try to drop unit 4050 from 0 th HD out of 71 possible.  usage down to 1.1271341676319715\n",
      "try to drop unit 4050 from 30 th HD out of 71 possible.  usage down to 1.1271341676319715\n",
      "all done trying to reduce usage of unit 4050 final usage = 1.12713 25 sec elapsed 0 6 successful, failed patches, couldn't start= 51\n",
      "current avg and SD of usage are 1.00604 0.05526\n",
      "starting to reduce usage for unit 2525 with usage 1.12651 . Total units tried = 30\n",
      "try to drop unit 2525 from 0 th HD out of 73 possible.  usage down to 1.1265132911299585\n",
      "all done trying to reduce usage of unit 2525 final usage = 1.01288 26 sec elapsed 11 0 successful, failed patches, couldn't start= 1\n",
      "current avg and SD of usage are 1.00594 0.05485\n",
      "starting to reduce usage for unit 1058 with usage 1.12531 . Total units tried = 31\n",
      "try to drop unit 1058 from 0 th HD out of 69 possible.  usage down to 1.1253050990179927\n",
      "try to drop unit 1058 from 30 th HD out of 69 possible.  usage down to 1.1098922593665175\n",
      "all done trying to reduce usage of unit 1058 final usage = 1.10989 26 sec elapsed 1 15 successful, failed patches, couldn't start= 40\n",
      "current avg and SD of usage are 1.00594 0.05461\n",
      "starting to reduce usage for unit 1044 with usage 1.12441 . Total units tried = 32\n",
      "try to drop unit 1044 from 0 th HD out of 60 possible.  usage down to 1.1244073451569492\n",
      "all done trying to reduce usage of unit 1044 final usage = 1.0181 30 sec elapsed 11 0 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00587 0.05396\n",
      "starting to reduce usage for unit 4081 with usage 1.12423 . Total units tried = 33\n",
      "try to drop unit 4081 from 0 th HD out of 73 possible.  usage down to 1.1242311504737457\n",
      "try to drop unit 4081 from 30 th HD out of 73 possible.  usage down to 1.0421076477472067\n",
      "all done trying to reduce usage of unit 4081 final usage = 1.01437 31 sec elapsed 8 46 successful, failed patches, couldn't start= 1\n",
      "current avg and SD of usage are 1.00585 0.05369\n",
      "starting to reduce usage for unit 2840 with usage 1.124 . Total units tried = 34\n",
      "try to drop unit 2840 from 0 th HD out of 30 possible.  usage down to 1.124004614452986\n",
      "all done trying to reduce usage of unit 2840 final usage = 1.07262 35 sec elapsed 7 12 successful, failed patches, couldn't start= 5\n",
      "current avg and SD of usage are 1.00581 0.05278\n",
      "starting to reduce usage for unit 2534 with usage 1.12363 . Total units tried = 35\n",
      "try to drop unit 2534 from 0 th HD out of 89 possible.  usage down to 1.1236270544179638\n",
      "all done trying to reduce usage of unit 2534 final usage = 1.01884 36 sec elapsed 11 4 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00573 0.05245\n",
      "starting to reduce usage for unit 2523 with usage 1.11978 . Total units tried = 36\n",
      "try to drop unit 2523 from 0 th HD out of 61 possible.  usage down to 1.1197843322837238\n",
      "try to drop unit 2523 from 30 th HD out of 61 possible.  usage down to 1.060532577455885\n",
      "all done trying to reduce usage of unit 2523 final usage = 1.0285 36 sec elapsed 7 21 successful, failed patches, couldn't start= 21\n",
      "current avg and SD of usage are 1.00568 0.05196\n",
      "starting to reduce usage for unit 1054 with usage 1.1165 . Total units tried = 37\n",
      "try to drop unit 1054 from 0 th HD out of 72 possible.  usage down to 1.1165037550906551\n",
      "try to drop unit 1054 from 30 th HD out of 72 possible.  usage down to 1.1165037550906551\n",
      "all done trying to reduce usage of unit 1054 final usage = 1.1165 36 sec elapsed 0 36 successful, failed patches, couldn't start= 22\n",
      "current avg and SD of usage are 1.00568 0.05196\n",
      "starting to reduce usage for unit 2792 with usage 1.11474 . Total units tried = 38\n",
      "try to drop unit 2792 from 0 th HD out of 77 possible.  usage down to 1.1147418082605758\n",
      "try to drop unit 2792 from 30 th HD out of 77 possible.  usage down to 1.0560521983737443\n",
      "all done trying to reduce usage of unit 2792 final usage = 1.00798 37 sec elapsed 7 31 successful, failed patches, couldn't start= 17\n",
      "current avg and SD of usage are 1.00567 0.05171\n",
      "starting to reduce usage for unit 8 with usage 1.10804 . Total units tried = 39\n",
      "try to drop unit 8 from 0 th HD out of 97 possible.  usage down to 1.108038020083412\n",
      "try to drop unit 8 from 30 th HD out of 97 possible.  usage down to 1.0781856066484863\n",
      "all done trying to reduce usage of unit 8 final usage = 1.01812 38 sec elapsed 7 24 successful, failed patches, couldn't start= 7\n",
      "current avg and SD of usage are 1.00564 0.05158\n",
      "starting to reduce usage for unit 2820 with usage 1.10285 . Total units tried = 40\n",
      "try to drop unit 2820 from 0 th HD out of 64 possible.  usage down to 1.1028528622691995\n",
      "all done trying to reduce usage of unit 2820 final usage = 1.0128 39 sec elapsed 7 4 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00559 0.05126\n",
      "starting to reduce usage for unit 2756 with usage 1.10138 . Total units tried = 41\n",
      "try to drop unit 2756 from 0 th HD out of 82 possible.  usage down to 1.1013845732441476\n",
      "try to drop unit 2756 from 30 th HD out of 82 possible.  usage down to 1.063435594613975\n",
      "try to drop unit 2756 from 60 th HD out of 82 possible.  usage down to 1.063435594613975\n",
      "all done trying to reduce usage of unit 2756 final usage = 1.05253 39 sec elapsed 4 53 successful, failed patches, couldn't start= 9\n",
      "current avg and SD of usage are 1.00556 0.05113\n",
      "starting to reduce usage for unit 10 with usage 1.10042 . Total units tried = 42\n",
      "try to drop unit 10 from 0 th HD out of 99 possible.  usage down to 1.1004196975991969\n",
      "try to drop unit 10 from 30 th HD out of 99 possible.  usage down to 1.1004196975991969\n",
      "try to drop unit 10 from 60 th HD out of 99 possible.  usage down to 1.1004196975991969\n",
      "all done trying to reduce usage of unit 10 final usage = 1.10042 40 sec elapsed 0 0 successful, failed patches, couldn't start= 80\n",
      "current avg and SD of usage are 1.00556 0.05113\n",
      "starting to reduce usage for unit 11 with usage 1.10042 . Total units tried = 43\n",
      "try to drop unit 11 from 0 th HD out of 99 possible.  usage down to 1.1004196975991969\n",
      "try to drop unit 11 from 30 th HD out of 99 possible.  usage down to 1.1004196975991969\n",
      "try to drop unit 11 from 60 th HD out of 99 possible.  usage down to 1.1004196975991969\n",
      "all done trying to reduce usage of unit 11 final usage = 1.10042 40 sec elapsed 0 0 successful, failed patches, couldn't start= 80\n",
      "current avg and SD of usage are 1.00556 0.05113\n",
      "starting to reduce usage for unit 543 with usage 1.10042 . Total units tried = 44\n",
      "try to drop unit 543 from 0 th HD out of 100 possible.  usage down to 1.1004196975991969\n",
      "try to drop unit 543 from 30 th HD out of 100 possible.  usage down to 1.1004196975991969\n",
      "try to drop unit 543 from 60 th HD out of 100 possible.  usage down to 1.1004196975991969\n",
      "all done trying to reduce usage of unit 543 final usage = 1.10042 41 sec elapsed 0 0 successful, failed patches, couldn't start= 80\n",
      "current avg and SD of usage are 1.00556 0.05113\n",
      "starting to reduce usage for unit 574 with usage 1.10042 . Total units tried = 45\n",
      "try to drop unit 574 from 0 th HD out of 100 possible.  usage down to 1.1004196975991969\n",
      "try to drop unit 574 from 30 th HD out of 100 possible.  usage down to 1.1004196975991969\n",
      "try to drop unit 574 from 60 th HD out of 100 possible.  usage down to 1.1004196975991969\n",
      "all done trying to reduce usage of unit 574 final usage = 1.10042 41 sec elapsed 0 0 successful, failed patches, couldn't start= 80\n",
      "current avg and SD of usage are 1.00556 0.05113\n",
      "starting to reduce usage for unit 4068 with usage 1.10042 . Total units tried = 46\n",
      "try to drop unit 4068 from 0 th HD out of 99 possible.  usage down to 1.1004196975991969\n",
      "try to drop unit 4068 from 30 th HD out of 99 possible.  usage down to 1.1004196975991969\n",
      "try to drop unit 4068 from 60 th HD out of 99 possible.  usage down to 1.1004196975991969\n",
      "all done trying to reduce usage of unit 4068 final usage = 1.10042 41 sec elapsed 0 0 successful, failed patches, couldn't start= 80\n",
      "current avg and SD of usage are 1.00556 0.05113\n",
      "starting to reduce usage for unit 4097 with usage 1.10042 . Total units tried = 47\n",
      "try to drop unit 4097 from 0 th HD out of 63 possible.  usage down to 1.1004196975991969\n",
      "try to drop unit 4097 from 30 th HD out of 63 possible.  usage down to 1.1004196975991969\n",
      "all done trying to reduce usage of unit 4097 final usage = 1.10042 42 sec elapsed 0 0 successful, failed patches, couldn't start= 51\n",
      "current avg and SD of usage are 1.00556 0.05113\n",
      "starting to reduce usage for unit 4156 with usage 1.10006 . Total units tried = 48\n",
      "try to drop unit 4156 from 0 th HD out of 86 possible.  usage down to 1.1000589180100684\n",
      "all done trying to reduce usage of unit 4156 final usage = 1.01877 43 sec elapsed 7 0 successful, failed patches, couldn't start= 1\n",
      "current avg and SD of usage are 1.00552 0.05095\n",
      "starting to reduce usage for unit 2856 with usage 1.0993 . Total units tried = 49\n",
      "try to drop unit 2856 from 0 th HD out of 65 possible.  usage down to 1.0992954077170904\n",
      "all done trying to reduce usage of unit 2856 final usage = 1.01643 43 sec elapsed 5 2 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00552 0.05088\n",
      "starting to reduce usage for unit 2877 with usage 1.09685 . Total units tried = 50\n",
      "try to drop unit 2877 from 0 th HD out of 82 possible.  usage down to 1.0968538528240683\n",
      "try to drop unit 2877 from 30 th HD out of 82 possible.  usage down to 1.0313765525300378\n",
      "try to drop unit 2877 from 60 th HD out of 82 possible.  usage down to 1.0313765525300378\n",
      "all done trying to reduce usage of unit 2877 final usage = 1.02631 44 sec elapsed 6 14 successful, failed patches, couldn't start= 46\n",
      "current avg and SD of usage are 1.0055 0.05077\n",
      "starting to reduce usage for unit 781 with usage 1.09465 . Total units tried = 51\n",
      "try to drop unit 781 from 0 th HD out of 83 possible.  usage down to 1.0946472241750478\n",
      "all done trying to reduce usage of unit 781 final usage = 1.00988 45 sec elapsed 8 0 successful, failed patches, couldn't start= 2\n",
      "current avg and SD of usage are 1.00545 0.05058\n",
      "starting to reduce usage for unit 3035 with usage 1.0942 . Total units tried = 52\n",
      "try to drop unit 3035 from 0 th HD out of 73 possible.  usage down to 1.0942025423560027\n",
      "all done trying to reduce usage of unit 3035 final usage = 1.01077 45 sec elapsed 6 12 successful, failed patches, couldn't start= 2\n",
      "current avg and SD of usage are 1.00548 0.05028\n",
      "starting to reduce usage for unit 3020 with usage 1.09087 . Total units tried = 53\n",
      "try to drop unit 3020 from 0 th HD out of 76 possible.  usage down to 1.0908716238248939\n",
      "try to drop unit 3020 from 30 th HD out of 76 possible.  usage down to 1.0587286795108957\n",
      "all done trying to reduce usage of unit 3020 final usage = 1.01473 45 sec elapsed 6 43 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00548 0.05019\n",
      "starting to reduce usage for unit 992 with usage 1.09069 . Total units tried = 54\n",
      "try to drop unit 992 from 0 th HD out of 80 possible.  usage down to 1.09068703891875\n",
      "try to drop unit 992 from 30 th HD out of 80 possible.  usage down to 1.082984814204507\n",
      "all done trying to reduce usage of unit 992 final usage = 1.0058 46 sec elapsed 7 5 successful, failed patches, couldn't start= 28\n",
      "current avg and SD of usage are 1.00543 0.05019\n",
      "starting to reduce usage for unit 2513 with usage 1.08789 . Total units tried = 55\n",
      "try to drop unit 2513 from 0 th HD out of 23 possible.  usage down to 1.08789309465978\n",
      "all done trying to reduce usage of unit 2513 final usage = 1.05283 51 sec elapsed 3 15 successful, failed patches, couldn't start= 1\n",
      "current avg and SD of usage are 1.0054 0.04968\n"
     ]
    }
   ],
   "source": [
    "#SECOND PATCHING BLOCK -- OVERUSERS.  applies a suppression of LONG STRINGS.  \n",
    "maxSD = 0.05 #0.06  #0.08  #0.04 \n",
    "print(maxSD,\"= default maxSD. Reco'ing 0.05 for blocky\")\n",
    "maxSD = float(input(\"enter maxSD\"))\n",
    "stopMaxUse = 1.02 #1.+  2.* maxSD  #0.5*maxSD  #don't be too aggressive; may create long chains\n",
    "print(\"default use threshold for moving on to next overused unit is\",r5(stopMaxUse) )\n",
    "stopMaxUse = float(input(\"enter updated stopMaxUse value\"))\n",
    "nInPlay = 0\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] > stopMaxUse:\n",
    "        nInPlay +=1\n",
    "print(\"there are currently\",nInPlay,\"units out of\",nUnits,\"with usage above\",stopMaxUse)\n",
    "nBigUsers = 5\n",
    "maxExchangePop = 0.25*aDP\n",
    "print(\"maxExchangePop is currently\",r5(maxExchangePop/aDP),\"fraction of avgDistrictPop\")\n",
    "print(\"this block reduces overuse, with exchanges up to\",int(maxExchangePop)) #\n",
    "maxGap = 0.9 * np.median(unitPop) # = aDP - minDistrictPop\n",
    "maxNtries = 0\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] > stopMaxUse:\n",
    "        maxNtries +=1\n",
    "currAvg, currSD = getWeightedAvgAndSD(unitUse,unitPop)\n",
    "nonfrozenList = list()\n",
    "for t in popHDlist:\n",
    "    if t not in hasSplitUnit: #hasSplitUnit[t] != 1:  #don't mess with the small number of HDs that have to have a split muni\n",
    "        nonfrozenList.append(t)\n",
    "        \n",
    "attemptedBigUs = list()\n",
    "print(\"current avg and SD of unit usage are\",r5(currAvg), r5(currSD),\". Now trying to reduce up to\",maxNtries,\"units' overusage\" )\n",
    "startTime = time.time()\n",
    "while currSD > maxSD and len(attemptedBigUs) < maxNtries: \n",
    "    #simplified vs. vanillaHD - just take the biggest overuser\n",
    "    eligUnitUse = unitUse.copy()\n",
    "    for u in range(nUnits):\n",
    "        if u in attemptedBigUs: #we already tried this one, so lock it out\n",
    "            eligUnitUse[u] = -999.  #preventing re-selection\n",
    "    OUU = eligUnitUse.index(np.max(eligUnitUse))\n",
    "    attemptedBigUs.append(OUU)  #so we don't try this unit again in a future loop\n",
    "    if unitPop[OUU] > 0.25 * aDP:  #some overusers are high-pop.  If so, will drop only this unit, not any neighbors\n",
    "        OUUc = [OUU]\n",
    "    else:\n",
    "        OUUc = [OUU] + unitNbrs[OUU]\n",
    "    print(\"starting to reduce usage for unit\",OUU,\"with usage\",r5(unitUse[OUU]),\". Total units tried =\",len(attemptedBigUs) )\n",
    "    for u in OUUc.copy():\n",
    "        if unitUse[u] < 1.:\n",
    "            OUUc.remove(u)  #...drop any underused neighbors of the primary OUU from the target sheddable cluster\n",
    "    OUUcSet = set( OUUc)  #for muni-snap, overused are isolated.  So don't bother adding two-level neighbors to cluster\n",
    "    ouuHDs, ouuDists = list(), list()\n",
    "    for t in nonfrozenList: #popHDlist:  #finding all HDs with at least one cluster member on the boundary\n",
    "        if OUU in HDunitList[t] and homeU[t] != OUU: #can't drop the home muni\n",
    "            HDadjoinSet =   set( getAdjoiners(HDunitList[t],unitNbrs) )\n",
    "            OUUcAdjoinSet = set( getAdjoiners(list(OUUcSet),unitNbrs) )\n",
    "            if len(HDadjoinSet.intersection(OUUcAdjoinSet) ) > 0: #the OUU or one of its overused 1-neighbors adjoins the complement\n",
    "                ouuHDs.append(t)  #so we can shed the OOUc to the complement\n",
    "                ouuDists.append( unitCP[OUU].distance(hdCP[t]) / avgDist[t] )\n",
    "    nPatchSuccess, nPatchFail, nCouldntStart, idxNo, idx0 = 0, 0, 0, 0, np.argsort(ouuDists)\n",
    "    while unitUse[OUU] > stopMaxUse and idxNo > -0.8*len(ouuHDs) : #arbitrarily only examine 80% of HDs, biasing farthest ones       \n",
    "        if idxNo % 30 == 0:\n",
    "            print(\"try to drop unit\",OUU,\"from\",abs(idxNo),\"th HD out of\",len(ouuHDs),\"possible.  usage down to\",unitUse[OUU] )\n",
    "        idxNo -=1\n",
    "        t = ouuHDs[idx0[idxNo]]\n",
    "        thisLoopOUUc = [OUU]\n",
    "        possibleOUUc = list((  OUUcSet.intersection(set(HDunitList[t]) )  ).difference( {homeU[t]} )) #again, homeU is untouchable\n",
    "        if np.sum([unitPop[u] for u in possibleOUUc]) < 0.25*aDP:\n",
    "            thisLoopOUUc = possibleOUUc.copy() #we can add the whole non-HDincluded cluster (-homeU) without exceeding 0.25 aDP            \n",
    "        trySet = set(HDunitList[t]).difference(set(thisLoopOUUc))\n",
    "        contig,complementContig, __, ___ = enclaveCheck(list(trySet), unitNbrs)\n",
    "        if not (contig and complementContig):  #dropping the cluster creates a problem (likely an HD discontig).  Try something simpler ...\n",
    "            if len(set(unitNbrs[OUU]).intersection(HDadjoinSet) )  > 0:  #Yay! The OUU itself on border.  Try dropping just it, not the full cluster\n",
    "                HDouuSet = {OUU}\n",
    "                trySet = set(HDunitList[t]).difference( {OUU} )\n",
    "                contig,complementContig, __, ___ = enclaveCheck(list(trySet), unitNbrs)\n",
    "        else:\n",
    "            HDouuSet = set(HDunitList[t]).intersection(set(thisLoopOUUc))  #set(OUUc)\n",
    "        if contig and complementContig:  #we can at least drop the cluster, let's go for more\n",
    "            #HDouuSet = set(HDunitList[t]).intersection(set(OUUc))  #the subset of the OUU cluster that's in this HD.  Defined above\n",
    "            HDouuCpop = np.sum([unitPop[u] for u in HDouuSet])\n",
    "            giveUpOnShedding = False            \n",
    "            shedCandidates, shedScores = list(), list()\n",
    "            bdryCandidates = getBdryNonEdgers(trySet, unitNbrs)  #new - any boundary unit can be shed, even if far from OUUc\n",
    "            for u in bdryCandidates:\n",
    "                if HDouuCpop + unitPop[u] <= maxExchangePop and u != homeU[t]:\n",
    "                    shedCandidates.append(u)\n",
    "                    shedScores.append((unitUse[u] - 1.) * unitCP[u].distance(hdCP[t])/avgDist[t])  #bias toward far, overused\n",
    "            if len(shedCandidates) == 0:\n",
    "                giveUpOnShedding = True\n",
    "            while HDouuCpop < maxExchangePop and not giveUpOnShedding:\n",
    "                idx, ij, notYetPicked = np.argsort(shedScores), 0, True\n",
    "                while ij < len(shedScores) and notYetPicked:\n",
    "                    listNo = idx[-1-ij]   #work from high to low score\n",
    "                    shedU = shedCandidates[listNo]\n",
    "                    if shedScores[listNo] <= 0:  #we're delving into the underused; stop adding to shed list\n",
    "                        break\n",
    "                    contig,cContig, __, ___ = enclaveCheck(list(trySet.difference({shedU}) ), unitNbrs)\n",
    "                    if contig and cContig:\n",
    "                        notYetPicked = False\n",
    "                        HDouuCpop += unitPop[shedU]\n",
    "                        #print(\"shedding unit\",shedU,\"from HD\",t,\"total shed Pop now\", HDouuCpop)\n",
    "                        HDouuSet.add(shedU)\n",
    "                        trySet.remove(shedU)\n",
    "                        del shedScores[shedCandidates.index(shedU)]\n",
    "                        del shedCandidates[shedCandidates.index(shedU)]\n",
    "                        newSheddables = set(unitNbrs[shedU]).intersection(trySet)\n",
    "                        for u in newSheddables:\n",
    "                            if HDouuCpop + unitPop[u] <= maxExchangePop and u not in shedCandidates and u != homeU[t]:\n",
    "                                shedCandidates.append(u)\n",
    "                                shedScores.append((unitUse[u] - 1.) * unitCP[u].distance(hdCP[t])/avgDist[t])\n",
    "                    else:\n",
    "                        ij +=1\n",
    "                if notYetPicked:\n",
    "                    giveUpOnShedding = True  #all candidates would create a discontig, so can't shed any more units\n",
    "            shedSet = HDouuSet.copy()  #set(OUUc).intersection(set(HDunitList[t]))\n",
    "            trySet = set(HDunitList[t]).difference(shedSet) \n",
    "            gap = aDP - np.sum([unitPop[u] for u in trySet])\n",
    "            nearHDlist, nearHDscore = list(), list()  #these will be dynamic lists of the nearby underused units\n",
    "            for u in trySet:\n",
    "                for uu in unitNbrs[u]:\n",
    "                    if uu not in HDunitList[t] and uu not in nearHDlist and unitPop[uu] < gap + maxGap and unitUse[uu] < 1.01:\n",
    "                        nearHDlist.append(uu)\n",
    "                        nearHDscore.append(5.*(unitUse[uu]-1.) + unitCP[uu].distance(hdCP[t]) / avgDist[t] )\n",
    "                        #bias toward UNDERUSED, close\n",
    "            addedSet = set( )    \n",
    "            stillGoing = True \n",
    "            while gap > maxGap and len(nearHDlist) > 0 and stillGoing:   #add the lowest-scoring neighboring underused unit until we've roughly squared the HDpop\n",
    "                nearHDscore2 = nearHDscore.copy()\n",
    "                for ij, uu in enumerate(nearHDlist):\n",
    "                    nHDnbrs = len( set(unitNbrs[uu]).intersection(trySet) )\n",
    "                    if nHDnbrs == 1 :  #BIAS AGAINST CREATING A SLIM CHAIN\n",
    "                        nearHDscore2[ij] *= 0.5   #make this score closer to zero (less negative) \n",
    "                idx, ij, notYetPicked = np.argsort(nearHDscore2), 0, True   #originally, used nearHDscore itself here\n",
    "                while ij < len(nearHDscore) and notYetPicked:        \n",
    "                    listNo = idx[ij]   #nearHDscore.index(np.min(nearHDscore))\n",
    "                    unitNoToAdd = nearHDlist[listNo]  #add this unit ...                            \n",
    "                    canAdd  = wontEnclave(unitNoToAdd, list(trySet), unitNbrs, borderUnits)\n",
    "                    if canAdd:\n",
    "                        notYetPicked = False\n",
    "                    else:\n",
    "                        ij +=1\n",
    "                if notYetPicked:\n",
    "                    stillGoing = False  #can't add any more units; we can't without creating an enclave\n",
    "                else:\n",
    "                    gap -= unitPop[unitNoToAdd]\n",
    "                    addedSet.add(unitNoToAdd)\n",
    "                    trySet.add( unitNoToAdd)\n",
    "                    for uu in unitNbrs[unitNoToAdd]:             # ... and add its nonHD neighbors to future candidates\n",
    "                        if uu not in trySet and uu not in nearHDlist and unitPop[uu] < gap + maxGap and unitUse[uu] < 1.01:  \n",
    "                            nearHDlist.append(uu)\n",
    "                            nearHDscore.append(5.* (unitUse[uu]-1.) + unitCP[uu].distance(hdCP[t]) / avgDist[t] ) \n",
    "                            #bias toward UNDERUSED, ~close\n",
    "                    del nearHDscore[nearHDlist.index(unitNoToAdd)]        \n",
    "                    del nearHDlist[ nearHDlist.index(unitNoToAdd) ]\n",
    "                    for ijj, uu in enumerate(nearHDlist.copy()):\n",
    "                        if unitPop[uu] > gap + maxGap:   #with the added pop from another unit, this unit is now too big to add\n",
    "                            del nearHDscore[nearHDlist.index(uu)]\n",
    "                            del nearHDlist[ nearHDlist.index(uu)]\n",
    "            currPop = np.sum([unitPop[u] for u in trySet])\n",
    "            if abs(currPop - aDP) <= maxGap:\n",
    "                for u in shedSet:\n",
    "                    unitUse[u] -= HDweight[t] * nDistricts\n",
    "                for u in addedSet:\n",
    "                    unitUse[u] += HDweight[t] * nDistricts\n",
    "                HDunitList[t] = list(trySet)\n",
    "                HDvPop[t]    = currPop\n",
    "                nPatchSuccess +=1\n",
    "            else:\n",
    "                nPatchFail +=1\n",
    "            # end of shed + add patching on this HD\n",
    "            #print(\"shed and patched for HD, OUU\",t,OUU)\n",
    "        else:\n",
    "            nCouldntStart +=1\n",
    "            #print(\"Due to discontiguity, can't drop OUU cluster for HD, OUU\", t, OUU)\n",
    "    print(\"all done trying to reduce usage of unit\",OUU,\"final usage =\",r5(unitUse[OUU]),int(time.time()-startTime),\"sec elapsed\",\n",
    "         nPatchSuccess,nPatchFail,\"successful, failed patches, couldn't start=\",nCouldntStart)\n",
    "    currAvg, currSD = getWeightedAvgAndSD(unitUse,unitPop)\n",
    "    print(\"current avg and SD of usage are\",r5(currAvg), r5(currSD) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "id": "35140f52-2cb9-40e6-be15-ac02ba88316c",
   "metadata": {},
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " patched use avg 1.0054 and SD 0.04968\n",
      "And here is the pop distro\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "checking contiguity of final HDs\n",
      "working on HD 0 out of 8941\n",
      "working on HD 800 out of 8941\n",
      "working on HD 1600 out of 8941\n",
      "working on HD 2400 out of 8941\n",
      "working on HD 3200 out of 8941\n",
      "working on HD 4000 out of 8941\n",
      "working on HD 4800 out of 8941\n",
      "working on HD 5600 out of 8941\n",
      "working on HD 6400 out of 8941\n",
      "working on HD 7200 out of 8941\n",
      "working on HD 8000 out of 8941\n",
      "working on HD 8800 out of 8941\n",
      "all done checking HD and complement contiguity for all 8941 HDs\n"
     ]
    }
   ],
   "source": [
    "patchedUse, unpUse, HDvPop = [0.]*nUnits, [0.]*nUnits, [0.]*nHDs\n",
    "for t in popHDlist:\n",
    "    if homeU[t] not in HDunitList[t]:\n",
    "        print(\"WARNING - we lost home unit\",homeU[t],\"from HD\",t)\n",
    "    for u in HDunitList[t]:\n",
    "        patchedUse[u] += HDweight[t] * nDistricts       \n",
    "        HDvPop[t] += unitPop[u]\n",
    "    if t in hasSplitUnit:\n",
    "        patchedUse[splitUnitNo[t]] -= (1. - splitUnitFrac[t]) * nDistricts * HDweight[t]\n",
    "        HDvPop[t]               -= (1. - splitUnitFrac[t]) * unitPop[splitUnitNo[t]]\n",
    "#    for u in unpatchedHDlist[t]:\n",
    "#        unpUse[u] += HDweight[t] * nDistricts\n",
    "plt.hist(patchedUse,bins=50, label=\"patched\",histtype=\"step\")\n",
    "#plt.hist(unpUse, bins=50, label=\"unpatched\",histtype=\"step\")\n",
    "plt.legend()\n",
    "plt.show()\n",
    "patchedAvg, patchedSD = getWeightedAvgAndSD(patchedUse,unitPop)\n",
    "#unpatchedAvg, unpatchedSD = getWeightedAvgAndSD(unpUse,unitPop)\n",
    "print(\" patched use avg\", r5(patchedAvg),\"and SD\",r5(patchedSD) )\n",
    "#print(\"unpatched, patched use avgs are\",r5(unpatchedAvg), r5(patchedAvg),\"and their SDs are\",r5(unpatchedSD), r5(patchedSD) )\n",
    "print(\"And here is the pop distro\")\n",
    "\n",
    "plt.hist([HDvPop[t] for t in popHDlist])\n",
    "plt.axvline(aDP, ls=\"--\",color=\"orange\")\n",
    "plt.axvline(0.95*aDP, ls=\"dotted\")\n",
    "plt.axvline(1.05*aDP, ls=\"dotted\")\n",
    "plt.show()\n",
    "print(\"checking contiguity of final HDs\")\n",
    "for t in popHDlist:\n",
    "    if t%800 == 0:\n",
    "        print(\"working on HD\",t,\"out of\",nHDs)\n",
    "    unbroken, noEnclave, sList, eList = enclaveCheck(HDunitList[t], unitNbrs)  #these HDunitLists now appear to be sets\n",
    "    if not unbroken or not noEnclave:\n",
    "        print(\"uh-oh, HD\",t,\"has contiguity, complement-contiguity of\",unbroken, noEnclave)\n",
    "print(\"all done checking HD and complement contiguity for all\",nHDs,\"HDs\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "id": "f81ae057-f060-4c95-9857-bcf3cfa8e82b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "another intermediate save - this time after patching, but still in HDunitList format\n"
     ]
    }
   ],
   "source": [
    "print(\"another intermediate save - this time after patching, but still in HDunitList format\")\n",
    "tList = [t for t in range(nHDs)]\n",
    "outDF = pd.DataFrame( {\"vtd\":tList,\"HDweight\":HDweight,\"HDvPop\":HDvPop,\"HDunitList\":HDunitList,\n",
    "                      \"splitUnitNo\":splitUnitNo,\"splitUnitFrac\":splitUnitFrac,\n",
    "                       \"centroid x\":HDCPx, \"centroid y\":HDCPy, \"homeU\":homeU, \"homeC\":homeC } )\n",
    "outname = STATE+str(int(nHDs))+\"_\"+str(nDistricts)+\"COI615patchedUnits.csv\" \n",
    "outpath = \"2024state_HD_output/\"+outname\n",
    "outDF.to_csv(outpath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "id": "72ce5734-f98b-4e84-9e95-144dcef7d674",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "OK, all HDs are contiguous and within pop tolerances\n",
      "Now, we need to assign blockgroups included in the HD for the 15 HDs with a split unit\n"
     ]
    }
   ],
   "source": [
    "print(\"OK, all HDs are contiguous and within pop tolerances\")\n",
    "print(\"Now, we need to assign blockgroups included in the HD for the\",len(hasSplitUnit),\"HDs with a split unit\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "id": "51ebd64b-0ff2-47d9-954d-3ef8e57cb454",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "17 2041 26\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "t = 17\n",
    "print(t, splitUnitNo[t],len(unitTractList[splitUnitNo[t]]) )\n",
    "contiggy = getContigFromStarter(unitTractList[splitUnitNo[t]][0],unitTractList[splitUnitNo[t]],bgNbrs)\n",
    "for bg in unitTractList[splitUnitNo[t]]:\n",
    "    plotPoly(tractGeom[bg])\n",
    "    if bg not in contiggy:\n",
    "        plotCenter(bg,tractGeom[bg])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "raw",
   "id": "0aa43d07-0fc9-4cfb-8137-6c23d4db93a1",
   "metadata": {},
   "source": [
    "problem to fix in below -- we may not have been contiggy to start"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 137,
   "id": "67ddf0bd-356d-4eac-9683-9eecae793e20",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{1163, 908, 661, 919, 921, 1436, 1437, 7853, 1199, 304, 689, 1459, 949, 1465, 704, 9408, 708, 9413, 9412, 6217, 1614, 718, 340, 1492, 4055, 3679, 1514, 880, 9457, 3577, 1918}\n",
      "{9457}\n",
      "set()\n"
     ]
    }
   ],
   "source": [
    "print(set(getAdjoiners(remContigBGs,bgNbrs)) )\n",
    "print(set(getAdjoiners(remContigBGs,bgNbrs)). intersection(maxBGset ) )\n",
    "print(set(getAdjoiners(remContigBGs,bgNbrs)). intersection(maxBGset.difference(remainingSet) ) ) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "id": "74202fa9-57f1-4af7-acec-386b7fb65245",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "t = hasSplitUnit[0]\n",
    "for u in HDunitList[t]:\n",
    "    for bg in unitTractList[u]:\n",
    "        plotPoly(tractGeom[bg],0.1)\n",
    "        plotCenter(u,tractGeom[bg],8)\n",
    "    if u == splitUnitNo[t]:\n",
    "        for bg in unitTractList[u]:\n",
    "            plotPoly(tractGeom[bg],1)\n",
    "plt.show()\n",
    "        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 144,
   "id": "d518d659-2194-4b48-813d-f2e65302f3b0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for bb in remContigBGs:\n",
    "    plotPoly(tractGeom[bb])\n",
    "plotCenter(bg,tractGeom[bg])\n",
    "plt.show()\n",
    "for bb in allContigBGs:\n",
    "    plotPoly(tractGeom[bb])\n",
    "plotCenter(bg,tractGeom[bg])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b3ed7b33-8f49-4f63-a58c-b59210b3fa90",
   "metadata": {},
   "outputs": [],
   "source": [
    "#11/24/24 - stuck in below, see #### for need to fix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 146,
   "id": "cf287ba6-b50f-4ad3-890f-41b3c7be1f13",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "OK, all HDs are contiguous and within pop tolerances\n",
      "Now, we need to assign blockgroups included in the HD for the 15 HDs with a split unit\n",
      "t,starterBG,len(contigBGsInWholeUs),len(BGsInWholeUs) 17 105 75 76\n",
      "17 11 t,len(sheddableSet)\n",
      "  all done assigning split-unit BGs for HD 17 pop/aDP is now 1.01\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "17 final HDpop = 120407 = 120407\n",
      "t,starterBG,len(contigBGsInWholeUs),len(BGsInWholeUs) 6950 835 77 77\n",
      "6950 14 t,len(sheddableSet)\n",
      "  all done assigning split-unit BGs for HD 6950 pop/aDP is now 1.019\n",
      "t,starterBG,len(contigBGsInWholeUs),len(BGsInWholeUs) 6951 835 77 77\n",
      "6951 14 t,len(sheddableSet)\n",
      "  all done assigning split-unit BGs for HD 6951 pop/aDP is now 1.011\n",
      "t,starterBG,len(contigBGsInWholeUs),len(BGsInWholeUs) 6958 835 77 77\n",
      "6958 14 t,len(sheddableSet)\n",
      "  all done assigning split-unit BGs for HD 6958 pop/aDP is now 1.019\n",
      "t,starterBG,len(contigBGsInWholeUs),len(BGsInWholeUs) 6962 835 77 77\n",
      "6962 14 t,len(sheddableSet)\n",
      "  all done assigning split-unit BGs for HD 6962 pop/aDP is now 1.011\n",
      "t,starterBG,len(contigBGsInWholeUs),len(BGsInWholeUs) 6964 835 77 77\n",
      "6964 14 t,len(sheddableSet)\n",
      "  all done assigning split-unit BGs for HD 6964 pop/aDP is now 1.011\n",
      "t,starterBG,len(contigBGsInWholeUs),len(BGsInWholeUs) 7093 835 77 77\n",
      "7093 14 t,len(sheddableSet)\n",
      "  all done assigning split-unit BGs for HD 7093 pop/aDP is now 1.012\n",
      "t,starterBG,len(contigBGsInWholeUs),len(BGsInWholeUs) 7118 835 77 77\n",
      "7118 14 t,len(sheddableSet)\n",
      "  all done assigning split-unit BGs for HD 7118 pop/aDP is now 1.012\n",
      "t,starterBG,len(contigBGsInWholeUs),len(BGsInWholeUs) 7191 330 75 76\n",
      "7191 11 t,len(sheddableSet)\n",
      "  all done assigning split-unit BGs for HD 7191 pop/aDP is now 1.019\n",
      "t,starterBG,len(contigBGsInWholeUs),len(BGsInWholeUs) 7218 330 75 76\n",
      "7218 11 t,len(sheddableSet)\n",
      "  all done assigning split-unit BGs for HD 7218 pop/aDP is now 1.016\n",
      "t,starterBG,len(contigBGsInWholeUs),len(BGsInWholeUs) 7253 105 75 76\n",
      "7253 11 t,len(sheddableSet)\n",
      "  all done assigning split-unit BGs for HD 7253 pop/aDP is now 1.018\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "7253 final HDpop = 121291 = 121291\n",
      "t,starterBG,len(contigBGsInWholeUs),len(BGsInWholeUs) 7298 320 75 76\n",
      "7298 11 t,len(sheddableSet)\n",
      "  all done assigning split-unit BGs for HD 7298 pop/aDP is now 1.005\n",
      "t,starterBG,len(contigBGsInWholeUs),len(BGsInWholeUs) 7511 835 77 77\n",
      "7511 14 t,len(sheddableSet)\n",
      "  all done assigning split-unit BGs for HD 7511 pop/aDP is now 1.012\n",
      "t,starterBG,len(contigBGsInWholeUs),len(BGsInWholeUs) 8153 105 75 76\n",
      "8153 11 t,len(sheddableSet)\n",
      "  all done assigning split-unit BGs for HD 8153 pop/aDP is now 1.011\n",
      "t,starterBG,len(contigBGsInWholeUs),len(BGsInWholeUs) 8171 105 75 76\n",
      "8171 11 t,len(sheddableSet)\n",
      "  all done assigning split-unit BGs for HD 8171 pop/aDP is now 1.01\n"
     ]
    }
   ],
   "source": [
    "print(\"OK, all HDs are contiguous and within pop tolerances\")\n",
    "print(\"Now, we need to assign blockgroups included in the HD for the\",len(hasSplitUnit),\"HDs with a split unit\")\n",
    "#tractCP = [tractGeom[b].centroid for b in range(nTracts)]  #should already be defined\n",
    "#      BELOW IS SIMILAR TO OH_muniSnap99, but using block group nomenclature\n",
    "\n",
    "splitBGlist = [list() for t in range(nHDs)] #each HD's final list of blockgroups from a split unit\n",
    "for i,t in enumerate(hasSplitUnit):\n",
    "    BGsInWholeUs = list()\n",
    "    for u in HDunitList[t]:\n",
    "        if u != splitUnitNo[t]:\n",
    "            BGsInWholeUs += unitTractList[u]\n",
    "    starterBG = BGsInWholeUs[0]  #this will be forced to be a bg in the majority contiguous piece\n",
    "    contigBGsInWholeUs = getContigFromStarter(starterBG,BGsInWholeUs,bgNbrs)  #the contig bgs in the group of whole units\n",
    "    while len(contigBGsInWholeUs) < 0.5 * len(BGsInWholeUs) : #we picked an isolated starter; need to pick a different one\n",
    "        remnantList = list(set(BGsInWholeUs).difference(set(contigBGsInWholeUs)) )\n",
    "        starterBG = remnantList[0]\n",
    "        contigBGsInWholeUs = getContigFromStarter(starterBG,remnantList,bgNbrs)\n",
    "    nContigWholeBGs = len(contigBGsInWholeUs) #the number of BGs in the largest contiguous piece of HDunitList excluding the splitU\n",
    "    print(\"t,starterBG,len(contigBGsInWholeUs),len(BGsInWholeUs)\",t,starterBG,len(contigBGsInWholeUs),len(BGsInWholeUs))\n",
    "        \n",
    "    if 1 == 1: #t in bridgeList: #strategy is to shed noncritical HDborder BGs until pop target met\n",
    "        maxBGset = set(unitTractList[homeU[t]])       \n",
    "        for u in HDunitList[t]:\n",
    "            maxBGset = maxBGset.union(set(unitTractList[u]))  #the set of bg's in the HD, PLUS if we added the whole split unit            \n",
    "        currPop = np.sum([tractPop[bg] for bg in maxBGset ] )  #... and the pop with all these splitU bg's included\n",
    "        \n",
    "        bridgeU = splitUnitNo[t]\n",
    "        remainingSet = set(unitTractList[bridgeU] )  #the BGs we have not yet shed from the split unit\n",
    "        sheddableSet, shedSet = set(), set()\n",
    "        \n",
    "        for bg in remainingSet:\n",
    "            #contig,cContig, _, __ = enclaveCheck( list(maxBGset.difference( shedSet.union({bg}) )),bgNbrs)\n",
    "            #  above won't work when the units were made from queen- but non-rook-contig units\n",
    "            proposedNotShedBridgeBGs = list( remainingSet.difference({bg}) )\n",
    "            proposedContigBGs = getContigFromStarter( starterBG,list(proposedNotShedBridgeBGs)+contigBGsInWholeUs, bgNbrs )\n",
    "            allContigBGs = getContigFromStarter( starterBG,list(remainingSet) + contigBGsInWholeUs, bgNbrs )\n",
    "            #print(t,bg,len(remContigBGs),len(allContigBGs),\"t,bg,len(remContigBGs),len(allContigBGs) \")\n",
    "            if len(proposedContigBGs) >= len(allContigBGs) - 1:  #dropping this splitU bg only reduces the contig set by 1, as expected\n",
    "                nonHDbgNbrs = set(bgNbrs[bg]).difference( maxBGset.difference(shedSet) )\n",
    "                if len(nonHDbgNbrs) > 0: #this candidate bg is on updated HD border\n",
    "                    sheddableSet.add(bg)  #... and this bg adjoins a non-HD unit.  Hence, we can shed it\n",
    "        print(t,len(sheddableSet),\"t,len(sheddableSet)\")    \n",
    "        while currPop > 1.02 * aDP and len(sheddableSet) > 0:\n",
    "            sheddableList = list(sheddableSet)\n",
    "            shedDist = [ tractCP[bg].distance(HDCP[t]) for bg in sheddableList ]\n",
    "            shedBG = sheddableList[shedDist.index(np.max(shedDist))]\n",
    "            #print(\"I shed vtd\",shedV)\n",
    "            currPop -= tractPop[shedBG]\n",
    "            sheddableSet.remove(shedBG)\n",
    "            remainingSet.remove(shedBG)\n",
    "            shedSet.add(shedBG)\n",
    "\n",
    "            ####\n",
    "            inUnitNbrs = set(bgNbrs[shedBG]).intersection(remainingSet) #newly border-facing vtds\n",
    "            for bg in inUnitNbrs:\n",
    "                proposedNotShedBridgeBGs = list( remainingSet.difference({bg}) )\n",
    "                proposedContigBGs = getContigFromStarter( starterBG,list(proposedNotShedBridgeBGs)+contigBGsInWholeUs, bgNbrs )\n",
    "                allContigBGs = getContigFromStarter(      starterBG,list(remainingSet)        + contigBGsInWholeUs,    bgNbrs )\n",
    "                #print(t,bg,len(remContigBGs),len(allContigBGs),\"t,bg,len(remContigBGs),len(allContigBGs) \")\n",
    "                if len(proposedContigBGs) >= len(allContigBGs) - 1:  #dropping this splitU bg only reduces the contig set by 1, as expected\n",
    "                    nonHDbgNbrs = set(bgNbrs[bg]).difference( maxBGset.difference(shedSet) )\n",
    "                    if len(nonHDbgNbrs) > 0: #this candidate bg is on updated HD border\n",
    "                        sheddableSet.add(bg)  #... and this bg adjoins a non-HD unit.  Hence, we can shed it\n",
    "\n",
    "                    #print(bg,\"is now in sheddable List\")\n",
    "        splitBGlist[t] = set(unitTractList[bridgeU]).difference(shedSet)\n",
    "        if len(hasSplitUnit) < 20:  #if here prevents massive printing\n",
    "            print(\"  all done assigning split-unit BGs for HD\",t,\"pop/aDP is now\",r3(currPop/aDP))\n",
    "        if i%10 == 0:\n",
    "            plotPoly(HDCP[t].buffer(0.01))\n",
    "            for u in HDunitList[t]:\n",
    "                plotPoly(unitGeom[u])\n",
    "            for b in splitBGlist[t]:\n",
    "                plotPoly(tractGeom[b],0.3)\n",
    "                plotCenter(\"in\",tractGeom[b],8)\n",
    "            for b in set(unitTractList[bridgeU]).difference(set(splitBGlist[t])):\n",
    "                plotCenter(b,tractCP[b],8)\n",
    "            plt.show()\n",
    "            print(t,\"final HDpop =\",np.sum([unitPop[u] for u in HDunitList[t]]) - np.sum([tractPop[b] for b in shedSet] ) ,\n",
    "                  \"=\",np.sum([unitPop[u] for u in HDunitList[t]]) - unitPop[bridgeU] + np.sum([tractPop[b] for b in splitBGlist[t]]) )\n",
    "        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "91f1020e-0c90-4a0e-8507-ed4e39b0b91b",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d4478d9e-7bc1-4c00-9590-32d09ae56142",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 148,
   "id": "04dd5198-d238-41cc-b57e-a946e3e74adb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "histogram of bg use\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "BGuse = [0.]*nTracts\n",
    "finalBGlist = [list() for t in range(nHDs)]\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        if splitUnitNo[t] == u:\n",
    "            for b in splitBGlist[t]:\n",
    "                finalBGlist[t].append(b)\n",
    "                BGuse[b] += nDistricts * HDweight[t]\n",
    "        else:\n",
    "            finalBGlist[t] += unitTractList[u]\n",
    "            for b in unitTractList[u]:\n",
    "                BGuse[b] += nDistricts * HDweight[t]\n",
    "popBGlist = list()\n",
    "for b in range(nTracts):\n",
    "    if b not in skipList:\n",
    "        popBGlist.append(b)\n",
    "plt.hist([BGuse[b] for b in popBGlist],weights= [tractPop[b] for b in popBGlist])\n",
    "print(\"histogram of bg use\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "id": "d98ae9cf-2b88-493b-a4a7-a323c342dfd7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "finalHDvPop = [np.sum([tractPop[v] for v in finalBGlist[t] ]) for t in range(nHDs)]\n",
    "plt.hist([finalHDvPop[t] for t in popHDlist])\n",
    "plt.axvline(aDP,ls= \"--\")\n",
    "plt.axvline(0.95*aDP, ls=\"dotted\")\n",
    "plt.axvline(1.05*aDP, ls=\"dotted\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 150,
   "id": "4e9173d8-7247-4cfc-a247-e9bb4a208ea6",
   "metadata": {},
   "outputs": [],
   "source": [
    "HDvPop = finalHDvPop.copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 151,
   "id": "59d332e1-2b4b-4e17-90ee-a9c023ee9bde",
   "metadata": {},
   "outputs": [],
   "source": [
    "for t in popHDlist:\n",
    "    if homeU[t] not in HDunitList[t]:\n",
    "        print(t,\"doesn't have home unit\",homeU[t],\"in its unit list. Its split muni no is\",splitUnitNo[t])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 155,
   "id": "bf2974d1-6e47-4f90-972a-e411471c6040",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "9472 8941 8941 8941\n"
     ]
    }
   ],
   "source": [
    "\n",
    "vtdPopFile = gpd.read_file(\"state_map_files/oh_pl2020_vtd.dbf\")  #use vtd's directly\n",
    "vtdGeom = vtdPopFile['geometry'] \n",
    "nVTDs = len(vtdGeom)\n",
    "vtdPop = vtdPopFile['P0010001'].to_numpy()\n",
    "vtdCN = vtdPopFile['COUNTYFP20']\n",
    "vtdCountyNo = list()\n",
    "for v in range(nVTDs):\n",
    "    vtdCountyNo.append( int((int(vtdCN[v]) - 1)/2) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 160,
   "id": "ca4f5b88-ff08-46ce-92d9-f4b71054a5bb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "now write the final bg lists to a file\n"
     ]
    }
   ],
   "source": [
    "print(\"now write the final bg lists to a file\")\n",
    "tList = [t for t in range(nHDs)]\n",
    "outDF = pd.DataFrame( {\"vtd\":tList,\"HDweight\":HDweight,\"HDvPop\":HDvPop,\"HDbgList\":finalBGlist,\n",
    "                      \"centroid x\":HDCPx, \"centroid y\":HDCPy,\"countyNo\":vtdCountyNo,\"splitUnitNo\":splitUnitNo} )\n",
    "outname = STATE+str(int(nHDs))+\"COI615legislPatchedBGs.csv\"\n",
    "outpath = \"2024state_HD_output/\"+outname\n",
    "outDF.to_csv(outpath)  #muni-based complete 11-11-24"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c42effd1-7ad5-49f1-b021-536f90ece7c4",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.14"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
